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Search results for: MULTI-CRITERION EVOLUTIONARY ALGORITHMS
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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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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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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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Waldemar Korłub dr inż.
PeopleWaldemar Korłub obtained an Eng. degree in 2011, MSc.Eng. degree in 2012 and PhD in Computer Science in 2017 granted by the Faculty of Electronics, Telecommunications and Informatics at Gdansk University of Technology. His research interests include: distributed systems mainly grid and cloud computing platforms, autonomous systems capable of self-optimization, self-management, self-healing and self-protection, artificial intelligence...
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Framework of an Evolutionary Multi-Objective Optimisation Method for Planning a Safe Trajectory for a Marine Autonomous Surface Ship
PublicationThis paper represents the first stage of research into a multi-objective method of planning safe trajectories for marine autonomous surface ships (MASSs) involved in encounter situations. Our method applies an evolutionary multi-objective optimisation (EMO) approach to pursue three objectives: minimisation of the risk of collision, minimisation of fuel consumption due to collision avoidance manoeuvres, and minimisation of the extra...
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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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Shape Optimisation of Kaplan Turbine Blades Using Genetic Algorithms
PublicationThis monograph is a comprehensive guide to a method of blade profile optimisation for Kaplan-type turbines. This method is based on modelling the interaction between rotor and stator blades. Additionally, the shape of the draft tube is investigated. The influence of the periodic boundary condition vs. full geometry is also discussed. Evolutionary algorithms (EA) are used as an optimisation method together with artificial neural...
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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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Ochrona odbiorników GNSS przed zakłóceniami celowymi
PublicationArtykuł dotyczy zastosowania algorytmów przestrzennego cyfrowego przetwarzania sygnałów dla potrzeb selektywnej eliminacji sygnałów zakłócających pracę odbiorników nawigacji satelitarnej GNSS. Omówiono podatność tych odbiorników na ataki elektroniczne typu zagłuszanie oraz spoofing. Polegają one na celowej emisji sygnałów niepożądanych w paśmie pracy systemu. Następnie przedstawiono koncepcję przeciwdziałania tego rodzaju zakłóceniom...
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METODA WIELOKRYTERIALNEJ OCENY PRZEBUDOWY UKŁADÓW TOROWYCH NA SZLAKACH
PublicationRozprawa doktorska dotyczy zagadnienia projektowania układów geometrycznych toru kolejowego w procesie modernizacji linii kolejowych. Scharakteryzowano główne cechy dotyczące tej tematyki w oparciu o literaturę polską i zagraniczną, w tym przepisy branżowe. Przedstawiono czynniki wpływające na projektowanie modernizacji linii kolejowych. Określono wartości dopuszczalne parametrów kinematycznych i geometrycznych. Specyfika omawianego...
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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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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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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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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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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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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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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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Preference-based evolutionary multi-objective optimization in ship weather routing
PublicationIn evolutionary multi-objective optimization (EMO) the aim is to find a set of Pareto-optimal solutions. Such approach may be applied to multiple real-life problems, including weather routing (WR) of ships. The route should be optimal in terms of passage time, fuel consumption and safety of crew and cargo while taking into account dynamically changing weather conditions. Additionally it must not violate any navigational constraints...
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A continual model of a damaged medium used for analyzing fatigue life of polycrystalline structural alloys under thermal–mechanical loading
PublicationThe main physical laws of thermal–plastic deformation and fatigue damage accumulation processes in polycrystalline structural alloys under various regimes of cyclic thermal–mechanical loading are considered. Within the framework of mechanics of damaged media, a mathematical model is developed that describes thermal–plastic deformation and fatigue damage accumulation processes under low-cycle loading. The model consists of three...
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Multi-agent graph searching and exploration algorithms
PublicationA team of mobile entities, which we refer to as agents or searchers interchangeably, starting from homebases needs to complete a given task in a graph.The goal is to build a strategy, which allows agents to accomplish their task. We analyze strategies for their effectiveness (e.g., the number of used agents, the total number of performed moves by the agents or the completion time).Currently, the fields of on-line (i.e., agents...
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Jarosław Sadowski dr hab. inż.
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Improving evolutionary multi-objective optimisation by niching
PublicationW pracy rozważa się ogólny problem optymalizacji ewolucyjnej i przestrzeniach wielowymiarowych, ze szczególnym uwzględnieniem mechanizmu niszowania, biorącego pod uwagę oceniane charakterystyki (funkcje przystosowania) osobników w generowanych nowych pokoleniach. Mechanizm ten służy do zapobiegania przedwczesnej zbieżności procedur ewolucyjnych poszukiwań oraz zwiększenia efektywności poszukiwań rozwiązań optymalnych. Polega on...
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Parallelization of Selected Algorithms on Multi-core CPUs, a Cluster and in a Hybrid CPU+Xeon Phi Environment
PublicationIn the paper we present parallel implementations as well as execution times and speed-ups of three different algorithms run in various environments such as on a workstation with multi-core CPUs and a cluster. The parallel codes, implementing the master-slave model in C+MPI, differ in computation to communication ratios. The considered problems include: a genetic algorithm with various ratios of master processing time to communication...
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Evolutionary approach to solving multi-ship encounter situations
PublicationW artykule wprowadzono nowe podejście do rozwiązywania sytuacji spotkań wielu statków poprzez połączenie założeń teorii gier z programowaniem ewolucyjnym. Spotkanie wielu statków jest zamodelowane jako gra rozgrywana przez ''myślących graczy'' - statki o różnych, potencjalnie zmiennych strategiach. Rozwiązanie - zbiór kooperujących (niekolidujących) trajektorii jest znajdowane za pomocą algorytmu ewolucyjnego.
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The Use of Evolutionary Algorithms for Optimization in the Modern Entrepreneurial Economy: Interdisciplinary Perspective
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Study of the Effectiveness of Model Order Reduction Algorithms in the Finite Element Method Analysis of Multi-port Microwave Structures
PublicationThe purpose of this paper is to investigate the effectiveness of model order reduction algorithms in finite element method analysis of multi-port microwave structures. Consideration is given to state of the art algorithms, i.e. compact reduced-basis method (CRBM), second-order Arnoldi method for passive-order reduction (SAPOR), reduced-basis methods (RBM) and subspace-splitting moment-matching MOR (SSMM-MOR)
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WiMA: Towards a Multi-Criterion Association in Software Defined Wi-Fi Networks
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Intelligent Optimization of Hard-Turning Parameters Using Evolutionary Algorithms for Smart Manufacturing
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Study of Multi-Class Classification Algorithms’ Performance on Highly Imbalanced Network Intrusion Datasets
PublicationThis paper is devoted to the problem of class imbalance in machine learning, focusing on the intrusion detection of rare classes in computer networks. The problem of class imbalance occurs when one class heavily outnumbers examples from the other classes. In this paper, we are particularly interested in classifiers, as pattern recognition and anomaly detection could be solved as a classification problem. As still a major part of...
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Genetics algorithms in multi-objective optimization of detection observer
PublicationW rozdziale przedstawia się możliwości zastosowania podejścia genetycznegodo zagadnień wielokryterialnej optymalizacji w przestrzeniach wielowymiaro-wych z wykorzystaniem koncepcji optymalności w sensie Pareto. Jako przykładilustrujący rozważane podejście daje się zadanie syntezy obserwatorów stanusłużących wykrywaniu błądów występujących w układzie sterowania bezzałogowe-go statku latającego oraz w układzie napędowym jednostki...
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Solving Multi-Ship Encounter Situations by Evolutionary Sets of Cooperating Trajectories
PublicationAutor zaproponował nowe podejście do sytuacji kolizyjnych na morzu. Polega ono na zastąpieniu ewolucyjnej trajektorii własnej ewolucyjnym zbiorem trajektorii wszystkich obiektów. Podejście to umożliwia predykcję manewrowania obiektów obcych przy jednoczesnym zachowaniu efektywności algorytmów ewolucyjnych. Dodatkowo, opracowany już wstępnie przez autorów zbiór kryteriów, ograniczeń i operatorów specjalizowanych powinien zapewnić...
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Spectral criterion of infinite fatigue life of machinery parts under multi-axial random loading
PublicationPrzedstawiono kryterium nieograniczonej trwałości zmęczeniowej metalowych elementów poddanych wieloosiowym losowym drganiom. W celu jego wyznaczenia zastosowano hipotezę energii odkształcenia postaciowego i równanie Goodmana/Soderberga. Traktując gęstości widmowe mocy składowych naprężenia jako znane, kryterium to sformułowano w dziedzinie częstości. W przykładzie obliczeniowym rozpatrzono okresowy w sensie średniokwadratowym stan...
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Evolutionary Sets of Cooperating Trajectories in Multi-Ship Encounter Situations - use cases
PublicationPrzedstawiono tu zalety nowego, proponowanego przez autora podejścia do sytuacji spotkań wielu statków na morzu. Podejście to polega na zastąpieniu ewolucyjnej trajektorii własnej ewolucyjnym zbiorem trajektorii wszystkich obiektów. Umożliwia to predykcję manewrowania obiektów obcych przy jednoczesnym zachowaniu efektywności algorytmów ewolucyjnych. Zaprezentowano kilka sytuacji nawigacyjnych należących do różnych kategorii spotkań...
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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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Improving evolutionary multi-objective optimisation using genders [Usprawnienie ewolucyjnej wielokryterialnej optymalizacji poprzez zastosowanie rodzajników]
PublicationW rozwiązywaniu wielkowymiarowych problemów wielokryterialnej optymalizacji za pomocą obliczeń ewolucyjnych (EMO) koncepcja dominacji w sensie Pareto nie jest efektywna. Dlatego w pracy rozważa się nowe podejście do rozwiązywania zadań wielokryterialnej optymalizacji metodą EMO, w którym wprowadza się pojęcie rodzajników genetycznych w celu rozróżnienia rozmaitych grup kryteriów oraz związanych z nimi subkryterialnych rozwiązań...
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Efkleidis Katsaros
PeopleEfklidis Katsaros received the B.Sc. degree in mathematics from the Aristotle University of Thessaloniki, Greece, in 2016, and the M.Sc. degree (cum laude) in data science: statistical science from Leiden University, The Netherlands, in 2019. He is currently pursuing the Ph.D. degree in deep video multi-task learning with the Department of Biomedical Engineering, Gdańsk University of Technology, Poland. Since 2020, he has been...
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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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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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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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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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Approximate Criteria for the Evaluation of Truly Multi-Dimensional Optimization Problems
PublicationIn this paper we propose new improved approximate quality criteria useful in assessing the efficiency of evolutionary multi-objective optimization (EMO). In the performed comparative study we take into account the various EMO algorithms of the state-of-the-art, in order to objectively assess the EMO performance in highly dimensional spaces. It is well known that useful executive criteria, such as those based on the true Pareto...
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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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Team Strategies - sem. 2022/23
e-Learning CoursesThe main aim of the course is to familiarize students with the basic problems in team strategies, such as: the use of the particle swarm optimization algorithms, the ant colony optimization, stochastic distributed searches, algorithms for team strategy, multi-agent systems, modeling intelligent cooperation, simulations of social behavior. The form of passing the course is passing the exam and completing a project task
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Team Strategies - sem. 2023/24
e-Learning CoursesThe main aim of the course is to familiarize students with the basic problems in team strategies, such as: the use of the particle swarm optimization algorithms, the ant colony optimization, stochastic distributed searches, algorithms for team strategy, multi-agent systems, modeling intelligent cooperation, simulations of social behavior. The form of passing the course is passing the exam and completing a project task
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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 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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Aestheticization of Flowcharts
PublicationOne of the important issues of diagrams is their aesthetics. In this paper a method of its formalization for freehand drawn flowcharts is proposed. In order to formalize the evaluation of flowcharts' aesthetics a criterion consisting of several measures is proposed. Based on this criterion the algorithms for automatic optimization of flowcharts' appearance are proposed.
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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...