Search results for: EVOLUTIONARY ALGORITHM
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Distributed Evolutionary Algorithm for Path Planning in Navigation Situation
PublicationThis article presents the use of a multi-population distributed evolutionary algorithm for path planning in navigation situation. The algorithm used is with partially exchanged population and migration between independently evolving populations. In this paper a comparison between a multi-population and a classic single-population algorithm takes place. The impact on the ultimate solution has been researched. It was shown that using...
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Evolutionary Algorithm for Selecting Dynamic Signatures Partitioning Approach
PublicationIn the verification of identity, the aim is to increase effectiveness and reduce involvement of verified users. A good compromise between these issues is ensured by dynamic signature verification. The dynamic signature is represented by signals describing the position of the stylus in time. They can be used to determine the velocity or acceleration signal. Values of these signals can be analyzed, interpreted, selected, and compared....
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Parameters of evolutionary algorithm in problem of collision avoidance at sea
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Evolutionary algorithm and decisional DNA for multiple travelling salesman problem
PublicationIn the real world, it is common to face optimization problems that have two or more objectives that must be optimized at the same time, that are typically explained in different units, and are in conflict with one another. This paper presents a hybrid structure that combines set of experience knowledge structures (SOEKS) and evolutionary algorithms, NSGA-II (Non-dominated Sorting Genetic Algorithm II), to solve multiple optimization...
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Genetic operators of evolutionary algorithm in problem of collision avoidance at sea
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Pareto Task Assignments by an Adaptive Quantum-based Evolutionary Algorithm AQMEA
PublicationW pracy scharakteryzowano state_of_the_art w zakresie kwantowych algorytmów ewolucyjnych. Scharakteryzowano zasady efektywnego projektowania tej klasy algorytmów genetycznych. Podano wyniki uzyskane za pomocą kwantowego algorytmu ewolucyjnego AQMEA w zakresie wyznaczanie przydziałów zadań optymalnych w sensie Pareto.
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Comparison of Single and Multi-Population Evolutionary Algorithm for Path Planning in Navigation Situation
PublicationIn this paper a comparison of single and multi-population evolutionary algorithm is presented. Tested algorithms are used to determine close to optimal ship paths in collision avoidance situation. For this purpose a path planning problem is defined. A specific structure of the individual path and fitness function is presented. Principle of operation of single-population and multi-population evolutionary algorithm is described....
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Task Assignments in Logistics by Adaptive Multi-Criterion Evolutionary Algorithm with Elitist Selection
PublicationAn evolutionary algorithm with elitist selection has been developed for finding Pareto-optimal task assignments in logistics. A multi-criterion optimization problem has been formulated for finding a set of Pareto- optimal solutions. Three criteria have been applied for evaluation of task assignment: the workload of a bottleneck machine, the cost of machines, and the numerical performance of system. The machine constraints have...
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A Multi-Fidelity Surrogate-Model-Assisted Evolutionary Algorithm for Computationally Expensive Optimization Problems
PublicationIntegrating data-driven surrogate models and simulation models of different accuracies (or fideli-ties) in a single algorithm to address computationally expensive global optimization problems has recently attracted considerable attention. However, handling discrepancies between simulation models with multiple fidelities in global optimization is a major challenge. To address it, the two major contributions of this paper include:...
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Application of a modified evolutionary algorithm for the optimization of data acquisition to improve the accuracy of a video-polarimetric system
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High level synthesis with adaptive evolutionary algorithm for solving reliability and thermal problems in reconfigurable microelectronic systems.
PublicationPraca dotyczy badań efektywności adaptacyjnego algorytmu ewolucyjnego (AEA)zastosowanego do syntezy wysokiego poziomu układów cyfrowych CMOS w celu zredukowania rozpraszanej przez nie mocy. W wyniku obniżenia poziomu mocy pobieranej przez układ mikroelektroniczny uzyskuje się zmniejszenie szczytowej i średniej temperatury układu scalonego co z kolei prowadzi do wzrostu niezawodności całego systemu. Podczas przeprowadzonych...
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Reducing average and peak temperatures of VLSI CMOS circuits by means of evolutionary algorithm applied to high level synthesis.
PublicationW pracy przedstawiono adaptacyjny algorytm ewolucyjny zastosowany do syntezy wysokiego poziomu układów cyfrowych CMOS w celu zredukowania pobieranej przez nie mocy. Prowadzi to do redukcji szczytowej i średniej temperatury układu scalonego. Dzięki temu uzyskuje się wzrost niezawodności projektowanych układów scalonych.
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Comparison of tuning procedures based on evolutionary algorithm for multi-region fuzzy-logic PID controller for non-linear plant
PublicationThe paper presents a comparison of tuning procedures for a multi-region fuzzy-logic controller used for nonlinear process control. This controller is composed of local PID controllers and fuzzy-logic mechanism that aggregates local control signals. Three off-line tuning procedures are presented. The first one focuses on separate tuning of local PID controllers gains in the case when the parameters of membership functions of fuzzy-logic...
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Zastosowanie algorytmu ewolucyjnego do uczenia neuronowego regulatora napięcia generatora synchronicznego. Evolutionary algorithm for training a neural network of synchronous generator voltage controller
PublicationNajpopularniejsza metoda uczenia wielowarstwowych sieci neuronowych -metoda wstecznej propagacji błędu - charakteryzuje się słabą efektywnością. Z tego względu podejmowane są próby stosowania innych metod do uczenia sieci. W pracy przedstawiono wyniki uczenia sieci realizującej regulator neuronowy, za pomocą algorytmu ewolucyjnego. Obliczenia symulacyjne potwierdziły dobrą zbieżność algorytmu ewolucyjnego w tym zastosowaniu.
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Termination functions for evolutionary path planning algorithm
PublicationIn this paper a study of termination functions (stop criterion) for evolutionary path planning algorithm is presented. Tested algorithm is used to determine close to optimal ship paths in collision avoidance situation. For this purpose a path planning problem is defined. A specific structure of the individual path and fitness function is presented. For the simulation purposes a close to real tested environment is created. Five...
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Multicriteria Evolutionary Weather Routing Algorithm in Practice
PublicationThe Multicriteria Evolutionary Weather Routing Algorithm (MEWRA) has already been introduced by the author on earlier TransNav 2009 and 2011 conferences with a focus on theoretical application to a hybrid-propulsion or motor-driven ship. This paper addresses the topic of possible practical weather routing applications of MEWRA. In the paper some practical advantages of utilizing Pareto front as a result of multicriteria optimization...
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Impact of Initial Population on Evolutionary Path Planning Algorithm
PublicationIn this paper an impact of initial population on evolutionary path planning algorithm is presented. Tested algorithm is used to determine close to optimal shippaths in collision avoidance situation. For this purpose a path planning problem is defined. A specific structure of the individual path and fitness function is presented. For the simulation purposes a close to real tested environment is created. Four tests are performed....
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Impact of Initial Population on Evolutionary Path Planning Algorithm
PublicationIn this paper an impact of initial population on evolutionary path planning algorithm is presented. Tested algorithm is used to determine close to optimal ship paths in collision avoidance situation. For this purpose a path planning problem is defined. A specific structure of the individual path and fitness function is presented. For the simulation purposes a close to real tested environment is created. Four tests are performed....
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Evolutionary Algorithms in MPLS network designing
PublicationMPLS technology become more and more popular especially in core networks giving great flexibility and compatibility with existing Internet protocols. There is a need to optimal design such networks and optimal bandwidth allocation. Linear Programming is not time efficient and does not solve nonlinear problems. Heuristic algorithms are believed to deal with these disadvantages and the most promising of them are Evolutionary Algorithms....
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Extinction Event Concepts for the Evolutionary Algorithms
PublicationThe main goal of this present paper is to propose a structure for a tool helping to determine how algorithm would react in a real live application, by checking it's adaptive capabilities in an extreme situation. Also a different idea of an additional genetic operator is being presented. As Genetic Algorithms are directly inspired by evolution, extinction events, which are elementary in our planet's development history, became...
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OPTIMISING RIG DESIGN FOR SAILING YACHTS WITH EVOLUTIONARY MULTIOBJECTIVE ALGORITHM
PublicationThe paper presents a framework for optimising a sailing yacht rig using Multi-objective Evolutionary Algorithms and for filtering obtained solutions by means of a Multi-criteria Decision Making method. A Bermuda sloop with discontinuous rig is taken under consideration as a model rig configuration. It has been decomposed into its elements and described by a set of control parameters to form a responsive model which can be used...
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Hybrid evolutionary partitioning algorithm for heat transfer enhancement in VLSI circuits
PublicationW niniejszym artykule przedstawiono metodę pozwalającą na polepszenie transferu ciepła z układu scalonego do otoczenia poprzez zwiększenie liczby połączeń zewnętrznych, co pozwoliło na polepszenie przewodności cieplnej układu scalonego. Dla osiągnięcia tego celu opracowano nowy, hybrydowy, ewolucyjny algorytm podziału (ang. Hybrid Evolutionary Partitioning Algorithm - HEPA). Obliczenia przeprowadzone dla wybranych przykładów testowych...
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Experimental research on evolutionary path planning algorithm with fitness function scaling for collision scenarios
PublicationThis article presents typical ship collision scenarios, simulated using the evolutionary path planning system and analyses the impact of the fitness function scaling on the quality of the solution. The function scaling decreases the selective pressure, which facilitates leaving the local optimum in the calculation process and further exploration of the solution space. The performed investigations have proved that the use of scaling...
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Multi-criterion decision making in distributed systems by quantum evolutionary algorithms
PublicationDecision making by the AQMEA (Adaptive Quantum-based Multi-criterion Evolutionary Algorithm) has been considered for distributed computer systems. AQMEA has been extended by a chromosome representation with the registry of the smallest units of quantum information. Evolutionary computing with Q-bit chromosomes has been proofed to characterize by the enhanced population diversity than other representations, since individuals represent...
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The Use of Evolutionary Algorithms for Optimization in the Modern Entrepreneurial Economy: Interdisciplinary Perspective
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Intelligent Optimization of Hard-Turning Parameters Using Evolutionary Algorithms for Smart Manufacturing
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Design and optimisation of combinational digital circuits using modified evolutionary algorithm.Projektowanie i optymalizacja kombinacyjnych układów cyfrowych przy użyciu zmodyfikowanego algorytmu ewolucyjnego.
PublicationW pracy przedstawiono możliwości projektowania i optymalizacji układów kombinacyjnych przy użyciu zmodyfikowanych algorytmów ewolucyjnych. Modyfikacja algorytmów polega na wprowadzeniu chromosomów wielowarstwowych i operatorów działających na nich. Wyniki projektowania czterech układów kombinacyjnych uzyskanych uzyskane tą metodą porównano z następującymi metodami opisanymi w literaturze jak: Mapy Karnaugh, metoda Quine-McCluskey...
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Evolutionary Sets of Safe Ship Trajectories: improving the method by adjusting evolutionary techniques and parameters
PublicationThe paper presents some of the evolutionary techniques used by the evolutionary sets of safe ship trajectories method. In general, this method utilizes a customized evolutionary algorithm to solve a constrained optimization problem. This problem is defined as finding a set of cooperating trajectories (here the set is an evolutionary individual) of all the ships involved in the encounter situation. The resulting trajectories are...
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Multi-criterion, evolutionary and quantum decision making in complex systems
PublicationMulti-criterion, evolutionary and quantum decision making supported by the Adaptive Quantum-based Multi-criterion Evolutionary Algorithm (AQMEA) has been considered for distributed complex systems. AQMEA had been developed to the task assignment problem, and then it has been applied to underwater vehicle planning as another benchmark three-criterion optimization problem. For evaluation of a vehicle trajectory three criteria have...
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Evolutionary Sets of Safe Ship Trajectories: problem dedicated operators
PublicationThe paper presents the optimization process of the evolutionary sets of safe ship trajectories method, with a focus on its problem-dedicated operators. The method utilizes a customized evolutionary algorithm to solve a constrained optimization problem. This problem is defined as finding a set of cooperating trajectories (a set is an evolutionary individual) of all the ships involved in the encounter situation. The resulting trajectories...
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Evolutionary music composition system with statistically modeled criteria
PublicationThe paper concerns an original evolutionary music composition system. On the basis of available solutions, we have selected a finite set of music features which appear to have a key impact on the quality of composed musical phrases. Evaluation criteria have been divided into rule-based and statistical sub-sets. Elements of the cost function are modeled using a Gaussian distribution defined by the expected value and variance obtained...
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Electronic nose algorithm design using classical system identification for odour intensity detection
PublicationThe two elements considered crucial for constructing an efficient environmental odour intensity monitoring systems are sensors and algorithms typically addressed to as electronic nose sensor (e-nose). Due to operational complexity of biochemical sensors developed in human bodies algorithms based on computational methods of artificial intelligence are typically considered superior to classical model based approaches in development...
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Path planning algorithm for ship collisions avoidance in environment with changing strategy of dynamic obstacles
PublicationIn this paper a path planning algorithm for the ship collision avoidance is presented. Tested algorithm is used to determine close to optimal ship paths taking into account changing strategy of dynamic obstacles. For this purpose a path planning problem is defined. A specific structure of the individual path and fitness function is presented. Principle of operation of evolutionary algorithm and based on it dedicated application...
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Neural modelling of dynamic systems with time delays based on an adjusted NEAT algorithm
PublicationA problem related to the development of an algorithm designed to find an architecture of artificial neural network used for black-box modelling of dynamic systems with time delays has been addressed in this paper. The proposed algorithm is based on a well-known NeuroEvolution of Augmenting Topologies (NEAT) algorithm. The NEAT algorithm has been adjusted by allowing additional connections within an artificial neural network and...
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EVOLUTIONARY MULTI–OBJECTIVE WEATHER ROUTING OF SAILBOATS
PublicationThe paper presents a multi-objective method, which optimises the route of a sailboat. The presented method makes use of an evolutionary multi-objective (EMO) algorithm, which performs the optimisation according to three objective functions: total passage time, a sum of all course alterations made during the voyage and the average angle of heel. The last two of the objective functions reflect the navigator’s and passenger’s comfort,...
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Mean Crossover in evolutionary path planning method for maritime collision avoidance
PublicationAbstract: This paper presents the use of mean crossover genetic operator for path planning using evolutionary algorithm for collision avoidance on sea. Mean crossover ensures widening of the possible solutions' set that can be achieved in comparison to exchange crossover variant. The research shown, that the mean crossover allows to achieve results independent from the initial generation and quicker transition of thealgorithm from...
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Porównanie algorytmów MGA i NGA do projektowania i optymlizacji kombinacyjnych układów cyfrowych z algorytmem MLCEA.
PublicationW artykule zaprezentowano porównanie algorytmów ewolucyjnych do projektowania i optymalizacji kombinacyjnych układów cyfrowych. Porównano algorytmy MGA (Multiobjective Genetic Algorithm) i NGA (Genetic Algorithm with N-cardinality Reprezentation) z utworzonym algorytmem MLCEA (Multi-Layer Chromosome Evolutionary Algorithm), bazującym na reprezentacji osobników w postaci chromosomów wielowarstwowych. Otrzymane wyniki dla algorytmu...
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Genetic Programming for Workload Balancing in the Comcute Grid System
PublicationA genetic programming paradigm is implemented for reliability optimization in the Comcute grid system design. Chromosomes are generated as the program functions and then genetic operators are applied for finding Pareto-suboptimal task assignment and scheduling. Results are compared with outcomes obtained by an adaptive evolutionary algorithm.
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Multi-objective Weather Routing with Customised Criteria and Constraints
PublicationThe paper presents a weather routing algorithm utilising a multi-objective optimisation with constraints, namely the Multi-objective Evolutionary Weather Routing Algorithm (MEWRA). In the proposed approach weather route recommendations can be made simultaneously e.g. for passage time, fuel consumption and safety of passage by means of Pareto optimisation. The sets of criteria and constraints in the optimisation process are fully...
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Multiobjective Aerodynamic Optimization by Variable-Fidelity Models and Response Surface Surrogates
PublicationA computationally efficient procedure for multiobjective design optimization with variable-fidelity models and response surface surrogates is presented. The proposed approach uses the multiobjective evolutionary algorithm that works with a fast surrogate model, obtained with kriging interpolation of the low-fidelity model data enhanced by space-mapping correction exploiting a few high-fidelity training points. The initial Pareto...
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EM-Driven Multi-Objective Optimization of Antenna Structures in Multi-Dimensional Design Spaces
PublicationFeasible multi-objective optimization of antenna structures is presented. An initial set of Pareto optimal solutions is found using a multi-objective evolutionary algorithm (MOEA) working with a fast surrogate antenna model obtained by kriging interpolation of coarse-discretization EM simulation data. To make the surrogate construction computationally feasible in multi-dimensional design space, the space subset containing non-dominated...
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Rotational Design Space Reduction for Cost-Efficient Multi-Objective Antenna Optimization
PublicationCost-efficient multi-objective design of antenna structures is presented. Our approach is based on design space reduction algorithm using auxiliary single-objective optimization runs and coordinate system rotation. The initial set of Pareto-optimal solutions is obtained by optimizing a response surface approximation model established in the reduced space using coarse-discretization EM simulation data. The optimization engine is...
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W-dominance: Tradeoff-inspired dominance relation for preference-based evolutionary multi-objective optimization
PublicationThe paper presents a method of incorporating decision maker preferences into multi-objective meta-heuristics. It is based on tradeoffcoefficients and extends their applicability from bi-objective to multi-objective. The method assumes that a decision maker specifies a priori each objective’s importance as a weight interval. Based on this, w-dominance relation is introduced, which extends Pareto dominance. By replacing reference...
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Komputerowa weryfikacja układów cyfrowych CMOS utworzonych z podukładów zasilanych ze źródeł o różnych wartościach napięcia
PublicationW pracy zaprezentowano wyniki komputerowej weryfikacji cyfrowego układu CMOS utworzonego z klastrów, z których każdy jest zasilany odpowiednio malejącymi wartościami napięć. Zbiór klastrów został utworzony przy pomocy algorytmu ECA (Evolutionary Clustering Algorithm) dla potrzeb redukcji mocy pobieranej ze źródła zasilającego. Otrzymane rozwiązanie, charakteryzujące się zmniejszeniem zapotrzebowania na moc, nie powoduje pogorszenia...
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Fast Multi-Objective Antenna Design Through Variable-Fidelity EM Simulations
PublicationA technique for fast multi-objective antenna optimization is introduced. A kriging interpolation surrogate constructed from sampled coarse-mesh EM simulations is utilized by multi-objective evolutionary algorithm (MOEA) to obtain the initial Pareto front approximation. The surrogate is defined in a subset of the original design space, determined by means of independently optimized individual objectives. Response correction techniques...
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Expedited Multi-Objective Design Optimization of Miniaturized Microwave Structures Using Physics-Based Surrogates
PublicationIn this paper, a methodology for fast multi-objective design optimization of compact microwave circuits is presented. Our approach exploits an equivalent circuit model of the structure under consideration, corrected through implicit and frequency space mapping, then optimized by a multi-objective evolutionary algorithm. The correction/optimization of the surrogate is iterated by design space confinement and segmentation based on...
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Wykorzystanie algorytmów ewolucyjnych do doboru wzmocnień rozszerzonego obserwatora prędkości maszyny indukcyjnej
PublicationW pracy opisano sposób doboru wzmocnień rozszerzonego obserwatora prędkości maszyny indukcyjnej przy wykorzystaniu algorytmów ewolucyjnych. Zaproponowano funkcję celu opartą na rozkładzie biegunów obserwatora. Ze względu na wpływ prędkości maszyny na dynamikę obserwatora zaproponowano dobór wzmocnień obserwatora dla różnych przedziałów prędkości. Dla poszczególnych przedziałów zaprezentowano wyniki doboru wzmocnień w postaci tabel...
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Testing Stability of Digital Filters Using Multimodal Particle Swarm Optimization with Phase Analysis
PublicationIn this paper, a novel meta-heuristic method for evaluation of digital filter stability is presented. The proposed method is very general because it allows one to evaluate stability of systems whose characteristic equations are not based on polynomials. The method combines an efficient evolutionary algorithm represented by the particle swarm optimization and the phase analysis of a complex function in the characteristic equation....
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Weather Hazard Avoidance in Modeling Safety of Motor-Driven Ship for Multicriteria Weather Routing
PublicationWeather routing methods find the most suitable ocean?s route for a vessel, taking into account changeable weather conditions and navigational constraints. In the multicriteria approach based on the evolutionary SPEA algorithm one is able to consider a few constrained criteria simultaneously. The approach applied for a ship with hybrid propulsions has already been presented by one of the authors on previous TransNav?2009. This time...
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Evolving neural network as a decision support system — Controller for a game of “2048” case study
PublicationThe paper proposes an approach to designing the neuro-genetic self-learning decision support system. The system is based on neural networks being adaptively learned by evolutionary mechanism, forming an evolved neural network. Presented learning algorithm enables for a selection of the neural network structure by establishing or removing of connections between the neurons, and then for a finding the beast suited values of the network...
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Design space reduction and variable-fidelity EM simulations for feasible Pareto optimization of antennas
PublicationA computationally efficient procedure for multi-objective optimization of antenna structures is presented. In our approach, a response surface approximation (RSA) model created from sampled coarse-discretization EM antenna simulations is utilized to yield an initial set of Pareto-optimal designs using a multi-objective evolutionary algorithm. The final Pareto front representation for the high-fidelity model is obtained using surrogate-based...
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Decisional DNA and Optimization Problem
PublicationMany researchers have proved that Decisional DNA (DDNA) and Set of Experience Knowledge Structure (SOEKS or SOE) is a technology capable of gathering information and converting it into knowledge to help decision-makers to make precise decisions in many ways. These techniques have a feature to combine with different tools, such as data mining techniques and web crawlers, helping organization collect information from different sources...
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Three-objective antenna optimization by means of kriging surrogates and domain segmentation
PublicationIn this paper, an optimization framework for multi-objective design of antenna structures is discussed which exploits data-driven surrogates, a multi-objective evolutionary algorithm, response correction techniques for design refinement, as well as generalized domain segmentation. The last mechanism is introduced to constrain the design space region subjected to sampling, which permits reduction of the number of training data samples...
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Machine Learning Assisted Interactive Multi-objectives Optimization Framework: A Proposed Formulation and Method for Overtime Planning in Software Development Projects
PublicationMachine Learning Assisted Interactive Multi-objectives Optimization Framework: A Proposed Formulation and Method for Overtime Planning in Software Development Projects Hammed A. Mojeed & Rafal Szlapczynski Conference paper First Online: 14 September 2023 161 Accesses Part of the Lecture Notes in Computer Science book series (LNAI,volume 14125) Abstract Software development project requires proper planning to mitigate risk and...
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On deterministic procedures for low-cost multi-objective design optimization of miniaturized impedance matching transformers
PublicationPurpose This paper aims to investigate deterministic strategies for low-cost multi-objective design optimization of compact microwave structures, specifically, impedance matching transformers. The considered methods involve surrogate modeling techniques and variable-fidelity electromagnetic (EM) simulations. In contrary to majority of conventional approaches, they do not rely on population-based metaheuristics, which permit lowering...
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Efficient Multi-Objective Simulation-Driven Antenna Design Using Co-Kriging
PublicationA methodology for fast multi-objective antenna optimization is presented. Our approach is based on response surface approximation (RSA) modeling and variable-fidelity electromagnetic (EM) simulations. In the design process, a computationally cheap RSA surrogate model constructed from sampled coarse-discretization EM antenna simulations is optimized using a multi-objective evolutionary algorithm. The initially determined Pareto...
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Navigational decision support system during approach manoeuvre in emergency STS transfer operation
PublicationThe paper is concerned with the problem of safe trajectory planning for approaching during emergency STS (Ship to Ship) transfer operation with oil spill. The safe trajectory means that the way points does not cross in the area of the environment with the static and dynamic obstacles and at the same time satisfies ship's stopping and speed deceleration performance. The evolutionary path planning algorithm is used to determine trajectory...
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Rapid multi-objective design optimisation of compact microwave couplers by means of physics-based surrogates
PublicationThe authors introduce a methodology for fast multi-objective design optimisation of miniaturised microwave couplers. The approach exploits the surrogate-based optimisation paradigm with an underlying low-fidelity model constructed from an equivalent circuit of the structure under consideration, corrected through implicit and frequency space mapping. A fast prediction tool obtained this way is subsequently optimised by a multi-objective...
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Low-Cost EM-Simulation-Driven Multi-Objective Optimization of Antennas
PublicationA surrogate-based method for efficient multi-objective antenna optimization is presented. Our technique exploits response surface approximation (RSA) model constructed from sampled low-fidelity antenna model (here, obtained through coarse-discretization EM simulation). The RSA model enables fast determination of the best available trade-offs between conflicting design goals. A low-cost RSA model construction is possible through...
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Multi-objective design optimization of antennas for reflection, size, and gain variability using kriging surrogates and generalized domain segmentation
PublicationCost-efficient multi-objective design optimization of antennas is presented. The framework exploits auxiliary data-driven surrogates, a multi-objective evolutionary algorithm for initial Pareto front identification, response correction techniques for design refinement, as well as generalized domain segmentation. The purpose of this last mechanism is to reduce the volume of the design space region that needs to be sampled in order...
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Low-Cost Multi-Objective Optimization Yagi-Uda Antenna in Multi-Dimensional Parameter Space
PublicationA surrogate-based technique for fast multi-objective optimization of a multi-parameter planar Yagi-Uda antenna structure is presented. The proposed method utilizes response surface approximation (RSA) models constructed using training samples obtained from evaluation of the low-fidelity antenna model. Utilization of the RSA models allowsfor fast determination of the best possible trade-offs between conflicting objectives in multi-objective...
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Rhamnolipid CMC Prediction
PublicationRelationships between the purity, pH, hydrophobicity (log Kow) of the carbon substrate, and the critical micelle concentration (CMC) of rhamnolipid type biosurfactants (RL) were investigated using a quantitative structure–property relationship (QSPR) approach and are presented here for the first time. Measured and literature CMC values of 97 RLs, representing biosurfactants at different stages of purification, were considered....
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Design Space Reduction for Expedited Multi-Objective Design Optimization of Antennas in Highly-Dimensional Spaces
PublicationA surrogate-based technique for efficient multi-objective antenna optimization is discussed. Our approach exploits response surface approximation (RSA) model constructed from low-fidelity antenna model data (here, obtained through coarse-discretization electromagnetic simulations). The RSA model enables fast determination of the best available trade-offs between conflicting design goals. The cost of RSA model construction for multi-parameter...
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Towards Rational Biosurfactant Design—Predicting Solubilization in Rhamnolipid Solutions
PublicationThe efficiency of micellar solubilization is dictated inter alia by the properties of the solubilizate, the type of surfactant, and environmental conditions of the process. We, therefore, hypothesized that using the descriptors of the aforementioned features we can predict the solubilization efficiency, expressed as molar solubilization ratio (MSR). In other words, we aimed at creating a model to find the optimal surfactant and...
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Computationally Efficient Multi-Objective Optimization of and Experimental Validation of Yagi-Uda Antenna
PublicationIn this paper, computationally efficient multi-objective optimization of antenna structures is discussed. As a design case, we consider a multi-parameter planar Yagi-Uda antenna structure, featuring a driven element, three directors, and a feeding structure. Direct optimization of the high-fidelity electromagnetic (EM) antenna model is prohibitive in computational terms. Instead, our design methodology exploits response surface...
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Domain segmentation for low-cost surrogate-assisted multi-objective design optimisation of antennas
PublicationAbstract: Information regarding the best possible design trade-offs of an antenna structure can be obtained through multiobjective optimisation (MO). Unfortunately, MO is extremely challenging if full-wave electromagnetic (EM) simulation models are used for performance evaluation. Yet, for the majority of contemporary antennas, EM analysis is the only tool that ensures reliability. This study introduces a procedure for accelerated...
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Size reduction of ultra-wideband antennas with efficiency and matching constraints
PublicationAntenna design is a multifaceted task that involves handling of various performance figures concerning both electrical performance of the structure as well as its geometry. Simultaneous control of several objectives through rigorous optimization is very challenging and virtually impossible through conventional approaches such as parameter sweeping. In this work, we investigate size reduction of ultra‐wideband antenna structures...
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Accelerated multi-objective design optimization of antennas by surrogate modeling and domain segmentation
PublicationMulti-objective optimization yields indispensable information about the best possible design trade-offs of an antenna structure, yet it is challenging if full-wave electromagnetic (EM) analysis is utilized for performance evaluation. The latter is a necessity for majority of contemporary antennas as it is the only way of achieving acceptable modeling accuracy. In this paper, a procedure for accelerated multi-objective design of...
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Expedited constrained multi-objective aerodynamic shape optimization by means of physics-based surrogates
PublicationIn the paper, computationally efficient constrained multi-objective design optimization of transonic airfoil profiles is considered. Our methodology focuses on fixed-lift design aimed at finding the best possible trade-offs between the two objectives: minimization of the drag coefficient and maximization of the pitching moment. The algorithm presented here exploits the surrogate-based optimization principle, variable-fidelity computational...
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Multicomponent ionic liquid CMC prediction
PublicationWe created a model to predict CMC of ILs based on 704 experimental values published in 43 publications since 2000. Our model was able to predict CMC of variety of ILs in binary or ternary system in a presence of salt or alcohol. The molecular volume of IL (Vm), solvent-accessible surface (Sˆ), solvation enthalpy (DsolvGN), concentration of salt (Cs) or alcohol (Ca) and their molecular volumes (Vms and Vma, respectively) were chosen...
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Ship weather routing featuring w-MOEA/D and uncertainty handling
PublicationThe paper presents a new version of evolutionary multi-objective weather routing (WR) for ships taking into account uncertainties of weather forecasts in route optimization. The method applies authors’ w-MOEA/D algorithm: MOEA/D framework incorporating Decision Maker’s (DM) preferences by means of w-dominance relation. Owing to this, DM preferences are taken into account throughout optimization, allowing the process to focus on...
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Hierarchical Estimation of Human Upper Body Based on 2D Observation Utilizing Evolutionary Programming and 'Genetic Memory'
PublicationNew method of the human body pose estimation based on single camera 2D observation is presented. It employs 3D model of the human body, and genetic algorithm combined with annealed particle filter for searching the global optimum of model state, best matching the object's 2D observation. Additionally, motion cost metric is employed, considering current pose and history of the body movement, favouring the estimates with the lowest...
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Multi-objective optimization of water quality, pumps operation, and storage sizing of water distribution systems
PublicationA multi-objective methodology utilizing the Strength Pareto Evolutionary Algorithm (SPEA2) linked to EPANET for trading-off pumping costs, water quality, and tanks sizing of water distribution systems is developed and demonstrated. The model integrates variable speed pumps for modeling the pumps operation, two water quality objectives (one based on chlorine disinfectant concentrations and one on water age), and tanks sizing cost...
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Evolutionary approach to ship's trajectory planning within Traffic Separation Schemes
PublicationThe paper presents the continuation of the author's research on evolutionary approach to ship trajectory planning. While the general problem of the evolutionary trajectory planning has already been solved, no one has yet touched one of its specific aspects: evolutionary trajectory planning within Traffic Separation Schemes. Traffic Separation Scheme (TSS) is a traffic-management route-system complying with rules of the International...
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Prediction of maximum tensile stress in plain-weave composite laminates with interacting holes via stacked machine learning algorithms: A comparative study
PublicationPlain weave composite is a long-lasting type of fabric composite that is stable enough when being handled. Open-hole composites have been widely used in industry, though they have weak structural performance and complex design processes. An extensive number of material/geometry parameters have been utilized for designing these composites, thereby an efficient computational tool is essential for that purpose. Different Machine Learning...
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t-SNE Highlights Phylogenetic and Temporal Patterns of SARS-CoV-2 Spike and Nucleocapsid Protein Evolution
PublicationWe propose applying t-distributed stochastic neighbor embedding to protein sequences of SARS-CoV-2 to construct, visualize and study the evolutionary space of the coronavirus. The basic idea is to explore the COVID-19 evolution space by using modern manifold learning techniques applied to evolutionary distances between variants. Evolutionary distances have been calculated based on the structures of the nucleocapsid and spike proteins.
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Evolutionary Sets of Safe Ship Trajectories: Evaluation of Individuals
PublicationThe paper presents a description of the evaluation phase of the Evolutionary Sets of Safe Ship Trajectories method. In general, the Evolutionary Sets of Safe Ship Trajectories method combines some of the assumptions of game theory with evolutionary programming and finds an optimal set of cooperating trajectories of all ships involved in an encounter situation. While developing a new version of this method, the authors decided to...
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An automatic selection of optimal recurrent neural network architecture for processes dynamics modelling purposes
PublicationA problem related to the development of algorithms designed to find the structure of artificial neural network used for behavioural (black-box) modelling of selected dynamic processes has been addressed in this paper. The research has included four original proposals of algorithms dedicated to neural network architecture search. Algorithms have been based on well-known optimisation techniques such as evolutionary algorithms and...
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Evolutionary Sets of Safe Ship Trajectories: Evaluation of Individuals
PublicationThe paper presents a description of the evaluation phase of the Evolutionary Sets of Safe Ship Trajectories method. In general, the Evolutionary Sets of Safe Ship Trajectories method combines some of the assumptions of game theory with evolutionary programming and finds an optimal set of cooperating trajectories of all ships involved in an encounter situation. While developing a new version of this method, the au-thors decided...
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On evolutionary computing in multi-ship trajectory planning, Applied Intelligence
PublicationThe paper presents the updated version of Evolutionary Sets of Safe Ship Trajectories: a method which applies evolutionary algorithms and some of the assumptions of game theory to solving ship encounter situations. For given positions and motion parameters of the ships,the method finds a near optimal set of safe trajectories of all ships involved in an encounter. The method works in real time and the solutions must be returned...
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Analyzing sets of phylogenetic trees obtained from bayesian MCMC process using topology metrics
PublicationThe reconstruction of evolutionary trees is one of the primary objectives in phylogenetics. Such a tree represents historical evolutionary relationship between different species or organisms. Tree comparisons are used for multiple purposes, from unveiling the history of species to deciphering evolutionary associations amongorganisms and geographical areas.In the paper, we describe a general method for comparing hylogenetic trees....
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Ship Evolutionary Trajectory Planning Method with Application of Polynomial Interpolation
PublicationPaper presents the application of evolutionary algorithms and polynomial interpolation in ship evolutionary trajectory planning method. Evolutionary algorithms allows to find a coIlision free trajectory in real time, while polynomial interpolation allows to model smooth trajectory which keeps continuity of velocity and acceleration values along path. Combination of this two methods allows to find trajectory, which under some assumptions,...
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Experimental Comparison of Straight Lines and Polynomial Interpolation Modeling Methods in Ship Evolutionary Trajectory Planning Problem
PublicationPaper presents the application of evolutionary algorithms and polynomial interpolation in ship evolutionary trajectory planning method and its comparison to classic approach, where trajectory is modeled by straight lines. Evolutionary algorithms are group of methods that allows\ to find a collision free trajectory in real time, while polynomial interpolation allows to model smooth trajectory, which keeps continuity of velocity...
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Analyzing sets of phylogenetic trees using metrics
PublicationThe reconstruction of evolutionary trees is one of the primary objectives in phylogenetics. Such a tree represents historical evolutionary relationships between different species or organisms. Tree comparisons are used for multiple purposes, from unveiling the history of species to deciphering evolutionary associations among organisms and geographical areas. In this paper, we describe a general method for comparing phylogenetictrees...
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Non-Coaxially Rotating Motion in Casson Martial along with Temperature and Concentration Gradients via First-Order Chemical Reaction
PublicationThe effect of non-coaxial rotation on the transport of mass subjected to first-order chemical reaction is studied analytically. The effects of thermal radiation, buoyancy, constructive and destructive chemical reactions along with Casson fluid in rotating frame are discussed. Time evolution of primary and secondary velocities, energy and solute particles are analyzed. The behavior of flow under the variation of intensity of magnetic...
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Some Optimization Methods for Simulations in Volunteer and Grid Systems
PublicationIn this chapter, some optimization methods have been presented for improving performance of simulations in the volunteer and grid computing system called Comcute. Some issues related to the cloud computing can be solved by presented approaches as well as the Comcute platform can be used to simulate execution of expensive and energy consuming long-term tasks in the cloud environment. In particular, evolutionary algorithms as well...
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ANALIZA I PROJEKTOWANIE UKŁADÓW STEROWANIA STERAMI STRUMIENIOWYMI STATKÓW Z ZASTOSOWANIEM SYSTEMU Z BAZĄ WIEDZY
PublicationŚwiatowa literatura dostarcza przykładów wskazujących na aktualność tematyki związanej z wykorzystaniem elementów sztucznej inteligencji w zastosowaniach morskich. Komisja Europejska finansuje projekty mające na celu poprawę konkurencyjności przemysłu okrętowego. W rozprawie podjęto tematykę związaną ze wspomaganiem projektowania podsystemów elektroenergetycznych statków. W rozprawie udowodniono przyjętą na wstępie tezę pracy:...
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Evolutionary sets of safe ship trajectories with speed reduction manoeuvres within traffic separation schemes
PublicationIn the previous paper the author presented the evolutionary ship trajectory planning method designed to support Traffic Separation Schemes (TSS). This time the extensions of this method are described which allow to combine evolutionary trajectory planning with speed reduction manoeuvres. On TSS regions with higher than usual density of traffic and smaller distances between ships, the course alterations alone are not always sufficient...
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ADOPTED ISOCHRONE METHOD IMPROVING SHIP SAFETY IN WEATHER ROUTING WITH EVOLUTIONARY APPROACH
PublicationThe paper is focused on adaptation of an isochrone method necessary for application to a weather routing system with evolutionary approach. Authors propose an adaptation of the isochrone method with area partitioning assuring that the route found by the adopted method would not cross land. In result, when applied to a weather routing system with evolutionary approach, this proposal facilitates creation of initial population, resulting...
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Evolutionary Sets Of Safe Ship Trajectories: A New Approach To Collision Avoidance
PublicationThe paper introduces a new method of solving multi-ship encounter situations for both open waters and restricted water regions. The method, called evolutionary sets of safe trajectories combines some of the assumptions of game theory with evolutionary programming and aims to find optimal set of safe trajectories of all ships involved in an encounter situation. In a two-ship encounter situation it enables the operator of an on-board...
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Gender approach to multi-objective optimization of detection systems by pre-selection of criteria
PublicationA novel idea of performing evolutionary computations for solving highly-dimensional multi-objective optimization (MOO) problems is proposed. The information about individual genders is applied. This information is drawn out of the fitness of individuals and applied during the parental crossover in the evolutionary multi-objective optimization (EMO) processes. The paper introduces the principles of the genetic-gender approach (GGA)...
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Gender approach to multi-objective optimization of detection systems by pre-selection of criteria
PublicationA novel idea of performing evolutionary computations for solving highly-dimensional multi-objective optimization (MOO) problems is proposed. The information about individual genders is applied. This information is drawn out of the fitness of individuals and applied during the parental crossover in the evolutionary multi-objective optimization (EMO) processes. The paper introduces the principles of the genetic-gender approach (GGA)...
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Evolutionary Sets of Safe Ship Trajectories: the Method's Development and Selected Reaserch Results
PublicationThe Evolutionary Sets of Safe Ship Trajectories is a method solving ship encounter situations. The method combines evolutionary approach to planning ship trajectory with some of the assumption of game theory. For given positions and motion parameters the method finds a near optimal set of safe trajectories of all ships involved in an encounter. This paper presents framework of the method and its development. Additionally, selected...
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Gender approach to multi-objective optimization of detection systems by pre-selection of criteria
PublicationA novel idea of performing evolutionary computations for solving highly-dimensional multi-objective optimization (MOO) problems is proposed. The information about individual genders is applied. This information is drawn out of the fitness of individuals and applied during the parental crossover in the evolutionary multi-objective optimization (EMO) processes. The paper introduces the principles of the genetic-gender approach (GGA)...
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COLREGS compliance in Evolutionary Sets of Cooperating Ship Trajectories
PublicationIn general, Evolutionary Sets of Cooperating Ship Trajectories combine some of the assumptions of game theory with evolutionary programming and aim to find optimal set of cooperating trajectoriesof all ships involved in an encounter situation. In a two-ship encounter situation the method enables the operator of an on-board collision-avoidance system to predict the most probable behaviour of atarget and to plan the own manoeuvres...
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Computational intelligence methods in production management
PublicationThis chapter presents a survey of selected computational intelligence methods used in production management. This group of methods includes, among others, approaches based on the artificial neural networks, the evolutionary algorithms, the fuzzy logic systems and the particle swarm optimization mechanisms. From the abovementioned methods particularly noteworthy are the evolutionary and the particle swarm algorithms, which are successfully...
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Evolutionary Ship Track Planning within Traffic Separation Schemes – Evaluation of Individuals
PublicationThe paper presents an extended version of the author’s Evolutionary Sets of Safe Ship Trajectories method. The method plans safe tracks of all ships involved in an encounter including speed reduction manoeuvres, if necessary, and taking into account Rule 10 of COLREGS, which specifies ships’ behaviour within Traffic Separation Schemes governed by IMO. The paper focuses on the evaluation phase of the evolutionary process and shows...
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Comparison of Selection Schemes in Evolutionary Method of Path Planning
PublicationThis article compares an impact of using various selection schemes on the quality of the solution for the problem of planning the path for a moving object using the evolutionary method. In study case problem of avoiding collisions at sea is analyzed. The modelled environment includes static constraints (lands, canals, etc.) and dynamic objects (moving ships). Article analyses behaviour of selection schemes in two similar environments...
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Gender approaches to evolutionary multi-objective optimization using pre-selection of criteria
PublicationA novel idea to perform evolutionary computations (ECs) for solving highly dimensional multi-objective optimization (MOO) problems is proposed. Following the general idea of evolution, it is proposed that information about gender is used to distinguish between various groups of objectives and identify the (aggregate) nature of optimality of individuals (solutions). This identification is drawn out of the fitness of individuals...
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Customized crossover in evolutionary sets of safe ship trajectories
PublicationThe paper presents selected aspects of evolutionary sets of safe ship trajectories-a method which applies evolutionary algorithms and some of the assumptions of game theory to solving ship encounter situations. For given positions and motion parameters of the ships, the method finds a near optimal set of safe trajectories of all ships involved in an encounter. The method works in real time and the solutions must be returned within...