Wyniki wyszukiwania dla: OPTIMIZATION PROBLEMS
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Swarm Algorithms in Modern Engineering Optimization Problems
PublikacjaComplexity of today engineering problems is constantly increasing. Scientists no longer are facing issues, for which simple, mathematical programming methods are sufficient. Issues like autonomic vehicle navigation or classification are considered to be challenging, and although there exist valid means to solve them, in some cases there still is some place for improvement. With emergence of a new type of optimization techniques...
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JABAT Middleware as a Tool for Solving Optimization Problems
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Selected Multiple Criteria Supply Chain Optimization Problems
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Approximate Criteria for the Evaluation of Truly Multi-Dimensional Optimization Problems
PublikacjaIn 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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Approximate Quality Criteria for Difficult Multi-Objective Optimization Problems
PublikacjaThis paper introduces approximate analytic quality criteria useful in assessing the efficiency of evolutionary multi-objective optimization (EMO) procedures. We present a summary of extensive research into computing. In the performed comparative study we take into account the various approaches of the state-of-the-art, in order to objectively assess the EMO performance in highly dimensional spaces; where some executive criteria,...
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Approximate Quality Criteria for Difficult Multi-Objective Optimization Problems
PublikacjaThis paper introduces approximate analytic quality criteria useful in assessing the efficiency of evolutionary multi-objective optimization (EMO) procedures. We present a summary of extensive research into computing. In the performed comparative study we take into account the various approaches of the state-of-the-art, in order to objectively assess the EMO performance in highly dimensional spaces; where some executive criteria,...
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International Journal of Combinatorial Optimization Problems and Informatics
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Extended Hopfield models of neural networks for combinatorial multiobjective optimization problems
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Solving highly-dimensional multi-objective optimization problems by means of genetic gender
PublikacjaPaper presents a computational optimization study using a genetic gender approach for solving multi-objective optimization problems of detection observers. In this methodology the information about an individual gender of all the considered solutions is applied for the purpose of making distinction between different groups of objectives. This information is drawn out of the fitness of individuals and applied during a current parental...
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Solving highly-dimensional multi-objective optimization problems by means of genetic gender
PublikacjaPaper presents a computational optimization study using a genetic gender approach for solving multi-objective optimization problems of detection observers. In this methodology the information about an individual gender of all the considered solutions is applied for the purpose of making distinction between different groups of objectives. This information is drawn out of the fitness of individuals and applied during a current parental...
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A Multi-Fidelity Surrogate-Model-Assisted Evolutionary Algorithm for Computationally Expensive Optimization Problems
PublikacjaIntegrating 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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Drawing Functions and NLP Algorithm Steps for Optimization Problems by using O&G Software.
PublikacjaPraca opisuje program służący do wizualizacji problemów programowania nieliniowego (funkcja celu, ograniczenia) oraz pracy rozwiązującego je algorytmu. Wizualizacja może być realizowana w przestrzeni dwu- lub trójwymiarowej.
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Bayesian Optimization for solving high-frequency passive component design problems
PublikacjaIn this paper, the performance of the Bayesian Optimization (BO) technique applied to various problems of microwave engineering is studied. Bayesian optimization is a novel, non-deterministic, global optimization scheme that uses machine learning to solve complex optimization problems. However, each new optimization scheme needs to be evaluated to find its best application niche, as there is no universal technique that suits all...
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International Workshop on Approximation Algorithms for Combinatorial Optimization Problems
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International Conference on Integration of Artificial Intelligence and Operations Research Techniques in Constraint Programming for Combinatorial Optimization Problems
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Multi-objective optimization of microextraction procedures
PublikacjaOptimization of extraction process requiresfinding acceptable conditions for many analytes and goodperformance in terms of process time or solvent consumption. These optimization criteria are oftencontradictory to each other, the performance of the system in given conditions is good for some criteriabut poor for others. Therefore, such problems require special assessment tools that allow to combinethese contradictory criteria into...
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Multi-objective optimization of expensive electromagnetic simulation models
PublikacjaVast majority of practical engineering design problems require simultaneous handling of several criteria. For the sake of simplicity and through a priori preference articulation one can turn many design tasks into single-objective problems that can be handled using conventional numerical optimization routines. However, in some situations, acquiring comprehensive knowledge about the system at hand, in particular, about possible...
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Constrained aerodynamic shape optimization using neural networks and sequential sampling
PublikacjaAerodynamic shape optimization (ASO) involves computational fluid dynamics (CFD)-based search for an optimal aerodynamic shape such as airfoils and wings. Gradient-based optimization (GBO) with adjoints can be used efficiently to solve ASO problems with many design variables, but problems with many constraints can still be challenging. The recently created efficient global optimization algorithm with neural network (NN)-based prediction...
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Expedited Simulation-Driven Multi-Objective Design Optimization of Quasi-Isotropic Dielectric Resonator Antenna
PublikacjaMajority of practical engineering design problems require simultaneous handling of several criteria. Although many of design tasks can be turned into single-objective problems using sufficient formulations, in some situations, acquiring comprehensive knowledge about possible trade-offs between conflicting objectives may be necessary. This calls for multi-objective optimization that aims at identifying a set of alternative, Pareto-optimal...
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Gender approach to multi-objective optimization of detection systems by pre-selection of criteria
PublikacjaA 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
PublikacjaA 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
PublikacjaA 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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Mariusz Kaczmarek dr hab. inż.
OsobyReceived M.Sc., Eng. in Electronics in 1995 from Gdansk University of Technology, Ph.D. in Medical Electronics in 2003 and habilitation in Biocybernetics and Biomedical Engineering in 2017. He was an investigator in about 13 projects receiving a number of awards, including four best papers, practical innovations (7 medals and awards) and also the Andronicos G. Kantsios Award and Siemens Award. Main research activities: the issues...
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Design of dimensionally stable composites using efficient global optimization method
PublikacjaDimensionally stable material design is an important issue for space structures such as space laser communication systems, telescopes, and satellites. Suitably designed composite materials for this purpose can meet the functional and structural requirements. In this paper, it is aimed to design the dimensionally stable laminated composites by using efficient global optimization method. For this purpose, the composite plate optimization...
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Gender approaches to evolutionary multi-objective optimization using pre-selection of criteria
PublikacjaA 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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Solar Photovoltaic Energy Optimization and Challenges
PublikacjaThe study paper focuses on solar energy optimization approaches, as well as the obstacles and concerns that come with them. This study discusses the most current advancements in solar power generation devices in order to provide a reference for decision-makers in the field of solar plant construction throughout the world. These technologies are divided into three groups: photovoltaic, thermal, and hybrid (thermal/photovoltaic)....
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Optimization of Wireless Networks for Resilience to Adverse Weather Conditions
PublikacjaIn this chapter, we consider how adverse weather conditions such as rain or fog affect the performance of wireless networks, and how to optimize these networks so as to make them robust to these conditions. We first show how to analyze the weather conditions in order to make them useful for network optimization modelling. Using an example realistic network, we show how to optimize two types of wireless networks: free-space optical...
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Solar Photovoltaic Energy Optimization and Challenges
PublikacjaThe study paper focuses on solar energy optimization approaches, as well as the obstacles and concerns that come with them. This study discusses the most current advancements in solar power generation devices in order to provide a reference for decision-makers in the field of solar plant construction throughout the world. These technologies are divided into three groups: photovoltaic, thermal, and hybrid (thermal/photovoltaic)....
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On deterministic procedures for low-cost multi-objective design optimization of miniaturized impedance matching transformers
PublikacjaPurpose 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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Scalability of surrogate-assisted multi-objective optimization of antenna structures exploiting variable-fidelity electromagnetic simulation models
PublikacjaMulti-objective optimization of antenna structures is a challenging task due to high-computational cost of evaluating the design objectives as well as large number of adjustable parameters. Design speedup can be achieved by means of surrogate-based optimization techniques. In particular, a combination of variable-fidelity electromagnetic (EM) simulations, design space reduction techniques, response surface approximation (RSA) models,...
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Zdzisław Kowalczuk prof. dr hab. inż.
OsobyW 1978 ukończył studia w zakresie automatyki i informatyki na Wydziale Elektroniki Politechniki Gdańskiej, następnie rozpoczął pracę na macierzystej uczelni. W 1986 obronił pracę doktorską, w 1993 habilitował się na Politechnice Śląskiej na podstawie pracy Dyskretne modele w projektowaniu układów sterowania. W 1996 mianowany profesorem nadzwyczajnym, w 2003 otrzymał tytuł profesora nauk technicznych. W 2006 założył i od tego czasu...
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RANS-based design optimization of dual-rotor wind turbines
PublikacjaPurpose An improvement in the energy efficiency of wind turbines can be achieved using dual rotors. Because of complex flow physics, the design of dual-rotor wind turbines (DRWTs) requires repetitive evaluations of computationally expensive partial differential equation (PDE) simulation models. Approaches for solving design optimization of DRWTs constrained by PDE simulations are investigated. The purpose of this study is to determine...
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Efficient knowledge-based optimization of expensive computational models using adaptive response correction
PublikacjaComputer simulation has become an indispensable tool in engineering design as they allow an accurate evaluation of the system performance. This is critical in order to carry out the design process in a reliable manner without costly prototyping and physical measurements. However, high-fidelity computer simulations are computationally expensive. This turns to be a fundamental bottleneck when it comes to design automation using numerical...
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Fast Multi-Objective Aerodynamic Optimization Using Sequential Domain Patching and Multifidelity Models
PublikacjaExploration of design tradeoffs for aerodynamic surfaces requires solving of multi-objective optimization (MOO) problems. The major bottleneck here is the time-consuming evaluations of the computational fluid dynamics (CFD) model used to capture the nonlinear physics involved in designing aerodynamic surfaces. This, in conjunction with a large number of simulations necessary to yield a set of designs representing the best possible...
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Marine and Cosmic Inspirations for AI Algorithms
PublikacjaArtificial Intelligence (AI) is a scientific area that currently sees an enormous growth. Various new algorithms and methods are developed and many of them meets practical, successful applications. Authors of new algorithms draw different inspirations. Probably the most common one is the nature. For example, Artificial Neural Networks were inspired by the structure of human brain and nervous system while the classic Genetic Algorithm...
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Globalized parametric optimization of microwave components by means of response features and inverse metamodels
PublikacjaSimulation-based optimization of geometry parameters is an inherent and important stage of microwave design process. To ensure reliability, the optimization process is normally carried out using full-wave electromagnetic (EM) simulation tools, which entails significant computational overhead. This becomes a serious bottleneck especially if global search is required (e.g., design of miniaturized structures, dimension scaling over...
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Recent advances in rapid multiobjective optimization of expensive simulation models in microwave and antenna engineering by Pareto front exploration
PublikacjaPractical engineering design problems are inherently multiobjective, that is, require simultaneous control of several (and often conflicting) criteria. In many situations, genuine multiobjective optimization is required to acquire comprehensive information about the system of interest. The most popular solution techniques are populationbased metaheuristics, however, they are not practical for handling expensive electromagnetic...
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Spectral measurement of birefringence using particle swarm optimization analysis
PublikacjaThe measurement of birefringence is useful for the examination of both technical and biological objects. One of the main problems is that the polarization state of light in birefringent media changes periodically. Without the knowledge of the period number, the birefringence of a given medium cannot be determined reliably. We propose to analyse the spectrum of light in order to determine the birefringence. We use a Particle Swarm...
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Efficient Simulation-Based Global Antenna Optimization Using Characteristic Point Method and Nature-Inspired Metaheuristics
PublikacjaAntenna structures are designed nowadays to fulfil rigorous demands, including multi-band operation, where the center frequencies need to be precisely allocated at the assumed targets while improving other features, such as impedance matching. Achieving this requires simultaneous optimization of antenna geometry parameters. When considering multimodal problems or if a reasonable initial design is not at hand, one needs to rely...
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Computationally Efficient Multi-Objective Optimization of and Experimental Validation of Yagi-Uda Antenna
PublikacjaIn 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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Michał Małafiejski dr hab. inż.
OsobyMichał Małafiejski urodził się w 1975 roku. Uzyskał tytuł zawodowy magistra inżyniera informatyka w 1999 roku. W 2002 roku uzyskał stopień doktora nauk technicznych w dyscyplinie informatyka, a w 2014 roku stopień doktora habilitowanego w tej samej dziedzinie. Obecnie pracuje jako profesor nadzwyczajny w Katedrze Algorytmów i Modelowania Systemów. Jest autorem licznych prac z zakresu informatyki teoretycznej i matematyki dyskretnej....
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Optimization algorithm and filtration using the adaptive TIN model at the stage of initial processing of the ALS point cloud
PublikacjaAirborne laser scanning (ALS) provides survey results in the form of a point cloud. The ALS point cloud is a source of data used primarily for constructing a digital terrain model (DTM). To generate a DTM, the set of ALS observations must be first subjected to the point cloud processing methodology. A standard methodology is composed of the following stages: acquisition of the ALS data, initial processing (including filtration),...
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Variable-fidelity CFD models and co-Kriging for expedited multi-objective aerodynamic design optimization
PublikacjaPurpose – Strategies for accelerated multi-objective optimization of aerodynamic surfaces are investigated, including the possibility of exploiting surrogate modeling techniques for computational fluid dynamic (CFD)-driven design speedup of such surfaces. The purpose of this paper is to reduce the overall optimization time. Design/methodology/approach – An algorithmic framework is described that is composed of: a search space reduction,...
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Designing of Track Axis Alignment with the Use of Satellite Measurements and Particle Swarm Optimization
PublikacjaDesigning of the track’s alignment is a key issue from the point of view of maintaining of proper geometries. The paper presents a design method for sections of railway line located in the horizontal arch. The method is adapted to the technique of mobile satellite measurements. The general principles of this measurement method have been described in the article. A project's solution has been presented using mathematical notation...
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The Way One Defines Specification Matters: On the Performance Criteria for Efficient Antenna Optimization in Aggregated Bi-Objective Setups
PublikacjaDesign of antenna structures for real-world applications is a challenging task that often involves addressing multiple design requirements at a time. Popular solution approaches to this class of problems include utilization of composite objectives. Although configuration of such functions has a significant effect on the cost and performance of the optimization, their specific structure is normally determined based on engineering...
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A Generalized SDP Multi-Objective Optimization Method for EM-Based Microwave Device Design
PublikacjaIn this article, a generalized sequential domain patching (GSDP) method for efficient multi-objective optimization based on electromagnetics (EM) simulation is proposed. The GSDP method allowing fast searching for Pareto fronts for two and three objectives is elaborated in detail in this paper. The GSDP method is compared with the NSGA-II method using multi-objective problems in the DTLZ series, and the results show the GSDP method...
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Atomistic Surrogate-Based Optimization for Simulation-Driven Design of Computationally Expensive Microwave Circuits with Compact Footprints
PublikacjaA robust simulation-driven design methodology for computationally expensive microwave circuits with compact footprints has been presented. The general method introduced in this chapter is suitable for a wide class of N-port un-conventional microwave circuits constructed as a deviation from classic design solutions. Conventional electromagnetic (EM) simulation-driven design routines are generally prohibitive when applied to numerically...
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Applications of semi-definite optimization in quantum information protocols
PublikacjaThis work is concerned with the issue of applications of the semi-definite programming (SDP) in the field of quantum information sci- ence. Our results of the analysis of certain quantum information protocols using this optimization technique are presented, and an implementation of a relevant numerical tool is introduced. The key method used is NPA discovered by Navascues et al. [Phys. Rev. Lett. 98, 010401 (2007)]. In chapter...
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Algorytmy Optymalizacji Dyskretnej - ed. 2021/2022
Kursy OnlineIn real-world applications, many important practical problems are NP-hard, therefore it is expedient to consider not only the optimal solutions of NP-hard optimization problems, but also the solutions which are “close” to them (near-optimal solutions). So, we can try to design an approximation algorithm that efficiently produces a near-optimal solution for the NP-hard problem. In many cases we can even design approximation algorithms...
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Evolutionary algorithm and decisional DNA for multiple travelling salesman problem
PublikacjaIn 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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Computational intelligence methods in production management
PublikacjaThis 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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Expedited antenna optimization with numerical derivatives and gradient change tracking
PublikacjaDesign automation has been playing an increasing role in the development of novel antenna structures for various applications. One of its aspects is electromagnetic (EM)-driven design closure, typically applied upon establishing the antenna topology, and aiming at adjustment of geometry parameters to boost the performance figures as much as possible. Parametric optimization is often realized using local methods given usually reasonable...
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Multimodal Particle Swarm Optimization with Phase Analysis to Solve Complex Equations of Electromagnetic Analysis
PublikacjaIn this paper, a new meta-heuristic method of finding roots and poles of a complex function of a complex variable is presented. The algorithm combines an efficient space exploration provided by the particle swarm optimization (PSO) and the classification of root and pole occurrences based on the phase analysis of the complex function. The method initially generates two uniformly distributed populations of particles on the complex...
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Optimization of the Hardware Layer for IoT Systems using a Trust Region Method with Adaptive Forward Finite Differences
PublikacjaTrust-region (TR) algorithms represent a popular class of local optimization methods. Owing to straightforward setup and low computational cost, TR routines based on linear models determined using forward finite differences (FD) are often utilized for performance tuning of microwave and antenna components incorporated within the Internet of Things systems. Despite usefulness for design of complex structures, performance of TR methods...
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Team Strategies - sem. 2022/23
Kursy OnlineThe 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
Kursy OnlineThe 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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Key issues in modeling and optimization of lignocellulosic biomass fermentative conversion to gaseous biofuels
PublikacjaThe industrial-scale production of lignocellulosic-based biofuels from biomass is expected to benefit society and the environment. The main pathways of residues processing include advanced hydrolysis and fermentation, pyrolysis, gasification, chemical synthesis and biological processes. The products of such treatment are second generation biofuels. The degree of fermentation of organic substances depends primarily on their composition...
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Zero-Pole Approach in Microwave Passive Circuit Design
PublikacjaIn this thesis, optimization strategies for design of microwave passive structures including filters, couplers, antenna and impedance transformer and construction of various surroogate models utilized to fasten the design proces have been discussed. Direct and hybrid optimization methodologies including space mapping and multilevel algorithms combined with various surrogate models at different levels of fidelity have been utilized...
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Preference-based evolutionary multi-objective optimization in ship weather routing
PublikacjaIn 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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Towards solving heterogeneous fleet vehicle routing problem with time windows and additional constraints: real use case study
PublikacjaIn advanced logistic systems, there is a need for a comprehensive optimization of the transport of goods, which would reduce costs. During past decades, several theoretical and practical approaches to solve vehicle routing problems (VRP) were proposed. The problem of optimal fleet management is often transformed to discrete optimization problem that relies on determining the most economical transport routes for a number of vehicles...
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Dynamic Route Discovery Using Modified Grasshopper Optimization Algorithm in Wireless Ad-Hoc Visible Light Communication Network
PublikacjaIn recent times, visible light communication is an emerging technology that supports high speed data communication for wireless communication systems. However, the performance of the visible light communication system is impaired by inter symbol interference, the time dispersive nature of the channel, and nonlinear features of the light emitting diode that significantly reduces the bit error rate performance. To address these problems,...
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Optimization of hybrid parallel application execution in heterogeneous high performance computing systems considering execution time and power consumption
PublikacjaMany important computational problems require utilization of high performance computing (HPC) systems that consist of multi-level structures combining higher and higher numbers of devices with various characteristics. Utilizing full power of such systems requires programming parallel applications that are hybrid in two meanings: they can utilize parallelism on multiple levels at the same time and combine together programming interfaces...
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Balanced Spider Monkey Optimization with Bi-LSTM for Sustainable Air Quality Prediction
PublikacjaA reliable air quality prediction model is required for pollution control, human health monitoring, and sustainability. The existing air quality prediction models lack efficiency due to overfitting in prediction model and local optima trap in feature selection. This study proposes the Balanced Spider Monkey Optimization (BSMO) technique for effective feature selection to overcome the local optima trap and overfitting problems....
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Application of Multivariate Adaptive Regression Splines (MARSplines) for Predicting Hansen Solubility Parameters Based on 1D and 2D Molecular Descriptors Computed from SMILES String
PublikacjaA new method of Hansen solubility parameters (HSPs) prediction was developed by combining the multivariate adaptive regression splines (MARSplines) methodology with a simple multivariable regression involving 1D and 2D PaDEL molecular descriptors. In order to adopt the MARSplines approach to QSPR/QSAR problems, several optimization procedures were proposed and tested. The effectiveness of the obtained models was checked via standard...
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Parallel tabu search for graph coloring problem
PublikacjaTabu search is a simple, yet powerful meta-heuristic based on local search that has been often used to solve combinatorial optimization problems like the graph coloring problem. This paper presents current taxonomy of patallel tabu search algorithms and compares three parallelization techniques applied to Tabucol, a sequential TS algorithm for graph coloring. The experimental results are based on graphs available from the DIMACS...
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Fast multi-objective design optimization of microwave and antenna structures using data-driven surrogates and domain segmentation
PublikacjaPurpose Strategies and algorithms for expedited design optimization of microwave and antenna structures in multi-objective setup are investigated. Design/methodology/approach Formulation of the multi-objective design problem oriented towards execution of the population-based metaheuristic algorithm within the segmented search space is investigated. Described algorithmic framework exploit variable fidelity modeling, physics- and...
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Proximal primal–dual best approximation algorithm with memory
PublikacjaWe propose a new modified primal–dual proximal best approximation method for solving convex not necessarily differentiable optimization problems. The novelty of the method relies on introducing memory by taking into account iterates computed in previous steps in the formulas defining current iterate. To this end we consider projections onto intersections of halfspaces generated on the basis of the current as well as the previous...
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Selected dynamic properties of adaptive proportional observer of induction motor state variables
PublikacjaThis paper presents problems related to the design and the stability of adaptive proportional observer which is used for estimation of magnetic flux and motor speed in sensorless control systems of induction motor. The gain matrix of the observer was chosen by genetic algorithm and alternatively by pole placement method. It has been shown that adaptive proportional observer is stable if the...
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KOALA Graph Theory Internet Service
PublikacjaKOALA has been created with the idea of C++ library templates, implementing a broad set of procedures in the fields of algorithmic graph theory and network problems in discreate optimization. During the C2NIWA project, a library has been greatly ectended, the code refactored and enclosed with the internet service available in the public repository of thr project. Today it contains interconnected educational materials in the form...
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Modified DNA polymerases for PCR troubleshooting
PublikacjaPCR has become an essential tool in biological science. However, researchers often encounter problems with difficult targets, inhibitors accompanying the samples, or PCR trouble related to DNA polymerase. Therefore, PCR optimization is necessary to obtain better results. One solution is using modified DNA polymerases with desirable properties for the experiments. In this article, PCR troubleshooting, depending on the DNA polymerase...
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Janusz Cieśliński prof. dr hab. inż.
OsobyUrodził się 15 kwietnia 1954 r. w Słupsku. Jest absolwentem Wydziału Budowy Maszyn Politechniki Gdańskiej (1978), z którą związał całe swoje życie zawodowe. W 1986 r. obronił doktorat, w 1997 r. – habilitację, w 2006 r. – uzyskał tytuł profesora. Pełnił funkcje prodziekana ds. nauki Wydziału Mechanicznego przez dwie kadencje (2002–2008) oraz kierownika: Katedry Maszyn Przemysłu Spożywczego (2002–2006), Katedry Ekoinżynierii i...
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Energy-Aware High-Performance Computing: Survey of State-of-the-Art Tools, Techniques, and Environments
PublikacjaThe paper presents state of the art of energy-aware high-performance computing (HPC), in particular identification and classification of approaches by system and device types, optimization metrics, and energy/power control methods. System types include single device, clusters, grids, and clouds while considered device types include CPUs, GPUs, multiprocessor, and hybrid systems. Optimization goals include various combinations of...
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Regularized Local Basis Function Approach to Identification of Nonstationary Processes
PublikacjaThe problem of identification of nonstationary stochastic processes (systems or signals) is considered and a new class of identification algorithms, combining the basis functions approach with local estimation technique, is described. Unlike the classical basis function estimation schemes, the proposed regularized local basis function estimators are not used to obtain interval approximations of the parameter trajectory, but provide...
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A decision-making system supporting selection of commanded outputs for a ship's propulsion system with a controllable pitch propeller
PublikacjaThe ship's operators have to make decisions regarding the values of commanded outputs (commanded engine speed and pitch ratio) which ensure maximum vessel speed and minimum fuel consumption. Obviously, the presented decision problems are opposed. Therefore, there is a need for a compromise solution that enables more flexible vessel voyage planning. This paper deals with development of a computer-aided system supporting selection...
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On the low-cost design of abbreviated multisection planar matching transformer
PublikacjaA numerically demanding wideband matching transformer composed of three nonuniform transmission lines (NUTLs) has been designed and optimized at a low computational cost. The computational feasibility of the design has been acquired through the exploitation of low-fidelity NUTL models in most steps of the design procedure and an implicit space mapping optimization engine, providing high accuracy results with only a handful of EM...
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Accurate Modeling of Frequency Selective Surfaces Using Fully-Connected Regression Model with Automated Architecture Determination and Parameter Selection Based on Bayesian Optimization
PublikacjaSurrogate modeling has become an important tool in the design of high-frequency structures. Although full-wave electromagnetic (EM) simulation tools provide an accurate account for the circuit characteristics and performance, they entail considerable computational expenditures. Replacing EM analysis by fast surrogates provides a way to accelerate the design procedures. Unfortunately, modeling of microwave passives is a challenging...
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Inline Microwave Filters With N+1 Transmission Zeros Generated by Frequency-Variant Couplings: Coupling-Matrix-Based Synthesis and Design
PublikacjaA general coupling-matrix-based synthesis methodology for inline Nth-order microwave bandpass filters (BPFs) with frequency-variant reactive-type couplings that generate N+1 transmission zeros (TZs) is presented in this brief. The proposed approach exploits the formulation of the synthesis problem as three inverse nonlinear eigenvalue problems (INEVPs) so that the coupling matrix is built from their sets of eigenvalues. For this...
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How can analysts use multicriteria decision analysis?
PublikacjaProper decision making in multifacitated situation is very challenging task. It is especially difficult if there are many alternatives and criteria that are often contradictory. Analytical chemistry and related sciences involve many situations where decisions on complex problems are made. The support tools may be the use of MCDA (Multi-criteria Decision Analysis) algorithms. They formalize the decision process, make it transparent...
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Comparison of reproduction strategies in genetic algorithm approach to graph searching
Publikacjagenetic algorithms (ga) are a well-known tool used to obtain approximate solutions to optimization problems. successful application of genetic algorithm in solving given problem is largely dependant on selecting appropriate genetic operators. selection, mutation and crossover techniques play a fundamental role in both time needed to obtain results and their accuracy. in this paper we focus on applying genetic algorithms in calculating...
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Optymalizacja strategii sieci inteligentnych agentów za pomocą programowania genetycznego w systemie rozproszonym realizującym paradygmat volunteer computing
PublikacjaDynamicznie rosnąca złożoność i wymagania w odniesieniu do rozproszonych systemów informatycznych utrudnia zarządzanie dostępnymi zasobami sprzętowymi i programistycznymi. Z tego powodu celem rozprawy jest opracowanie wielokryterialnej metody programowania genetycznego, która pozwala na optymalizację strategii zespołu inteligentnych agentów programistycznych w zakresie zarządzania systemem realizującym paradygmat volunteer computing....
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DETERMINATION OF OBJECTIVES FOR URBAN FREIGHT POLICY
PublikacjaBackground: Decisions regarding strategic planning of urban freight transport very often are based on superficial assumptions inadequately reflecting the actual character of encountered challenges. The trend may be observed to adapt isolated solutions without supporting measures and verification of expected outcomes. Selected urban freight solutions have a significant potential to alleviate transport related problems, but they...
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Simulation-driven design of compact ultra-wideband antenna structures
PublikacjaPurpose–The purpose of this paper is to investigate strategies and algorithms for expedited designoptimization and explicit size reduction of compact ultra-wideband (UWB) antennas.Design/methodology/approach–Formulation of the compact antenna design problem aiming atexplicit size reduction while maintaining acceptable electrical performance is presented. Algorithmicframeworks are described suitable for handling various design situations...
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Low-Cost Data-Driven Surrogate Modeling of Antenna Structures by Constrained Sampling
PublikacjaFull-wave electromagnetic (EM) analysis has become one of the major design tools for contemporary antenna structures. Although reliable, it is computationally expensive which makes automated simulation-driven antenna design (e.g., parametric optimization) difficult. This difficulty can be alleviated by utilization of fast and accurate replacement models (surrogates). Unfortunately, conventional data-driven modeling of antennas...
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Multiclass AdaBoost Classifier Parameter Adaptation for Pattern Recognition
PublikacjaThe article presents the problem of parameter value selection of the multiclass ``one against all'' approach of an AdaBoost algorithm in tasks of object recognition based on two-dimensional graphical images. AdaBoost classifier with Haar features is still used in mobile devices due to the processing speed in contrast to other methods like deep learning or SVM but its main drawback is the need to assembly the results of binary...
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Study of a Multicriterion Decision-Making Approach to the MQL Turning of AISI 304 Steel Using Hybrid Nanocutting Fluid
PublikacjaThe enormous use of cutting fluid in machining leads to an increase in machining costs, along with different health hazards. Cutting fluid can be used efficiently using the MQL (minimum quantity lubrication) method, which aids in improving the machining performance. This paper contains multiple responses, namely, force, surface roughness, and temperature, so there arises a need for a multicriteria optimization technique. Therefore,...
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On Tradeoffs Between Width- and Fill-like Graph Parameters
PublikacjaIn this work we consider two two-criteria optimization problems: given an input graph, the goal is to find its interval (or chordal) supergraph that minimizes the number of edges and its clique number simultaneously. For the interval supergraph, the problem can be restated as simultaneous minimization of the path width pw(G) and the profile p(G) of the input graph G. We prove that for an arbitrary graph G and an integer t ∈ {1,...
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Prenatal exposure to substance of abuse: A worldwide problem
PublikacjaSubstance abuse during pregnancy is an important public health issue affecting the mother and the growing infant. Preterm labor, miscarriage, abruption and postpartum hemorrhage are obstetric complications which have been associated with women who are dependent on abused substances. Moreover, women are also at an increased risk of medical problems such as poor nutrition, anemia, urinary tract infections as well as sexually transmitted...
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Boundary value problems for ordinary differential equations with deviated arguments
PublikacjaDyskutowane są równania różniczkowe z dwupunktowym nieliniowym warunkiem brzegowym z argumentami typu odchylonego. Podano warunki dostateczne które gwarantują iż problem wyjściowy ma kwazi-rozwiązania. Podano też warunki przy których problem ten ma rozwiązanie. Wyniki uzyskano stosując metodę iteracji monotonicznych.Badano też pewne nierówności różniczkowe z odchylonymi argumentami.
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Four-point boundary-value problems for differential-algebraic systems
PublikacjaBadane są czteropunktowe problemy brzegowe dla układów równań różniczkowo-algebraicznych. Stosując metodę iteracji monotonicznych, podano warunki dostateczne na istnienie rozwiązań (jednego lub ekstremalnych) takich problemów. Podano przykład ilustrujacy otrzymane wyniki teoretyczne.
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Fundamentals of Physics-Based Surrogate Modeling
PublikacjaChapter 1 was focused on data-driven (or approximation-based) modeling methods. The second major class of surrogates are physics-based models outlined in this chapter. Although they are not as popular, their importance is growing because of the challenges related to construction and handling of approximation surrogates for many real-world problems. The high cost of evaluating computational models, nonlinearity of system responses,...
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A 3D-FEM mesh technique for fast analysis of waveguide problems containing rotatable tuning elements
PublikacjaIn this paper a meshing technique for 3D Finite Element Method is presented. It allows for fast analysis and optimization of the waveguide structures, which contain rotatable tuning elements. In the proposed procedure a thin layer of varying cylindrical mesh buffer is introduced in order to reuse unchanged mesh and FEM matrices in the rest of the domain.
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Spiral Search Grasshopper Features Selection with VGG19-ResNet50 for Remote Sensing Object Detection
PublikacjaRemote sensing object detection plays a major role in satellite imaging and is required in various scenarios such as transportation, forestry, and the ocean. Deep learning techniques provide efficient performance in remote sensing object detection. The existing techniques have the limitations of data imbalance, overfitting, and lower efficiency in detecting small objects. This research proposes the spiral search grasshopper (SSG)...
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Constructing a map of an anonymous graph: applications of universal sequences
PublikacjaWe study the problem of mapping an unknown environmentrepresented as an unlabelled undirected graph. A robot (or automaton)starting at a single vertex of the graph G has to traverse the graph and return to its starting point building a map of the graph in the process. We are interested in the cost of achieving this task (whenever possible) in terms of the number of edge traversal made by the robot. Another optimization criteria...
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Network-aware Data Prefetching Optimization of Computations in a Heterogeneous HPC Framework
PublikacjaRapid development of diverse computer architectures and hardware accelerators caused that designing parallel systems faces new problems resulting from their heterogeneity. Our implementation of a parallel system called KernelHive allows to efficiently run applications in a heterogeneous environment consisting of multiple collections of nodes with different types of computing devices. The execution engine of the system is open for...
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Communication and Load Balancing Optimization for Finite Element Electromagnetic Simulations Using Multi-GPU Workstation
PublikacjaThis paper considers a method for accelerating finite-element simulations of electromagnetic problems on a workstation using graphics processing units (GPUs). The focus is on finite-element formulations using higher order elements and tetrahedral meshes that lead to sparse matrices too large to be dealt with on a typical workstation using direct methods. We discuss the problem of rapid matrix generation and assembly, as well as...
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Multiple solutions of boundary-value problems for fourth-order differential equations with deviating arguments
PublikacjaPraca dotyczy równań różniczkowych rzędu czwartego z warunkami brzegowymi i odchylonymi argumentami. Podano wystarczające warunki, dla których problemy dotyczące takich równań mają dodatnie rozwiązania. W pracy rozważa się przypadki kiedy argumenty odchylone są typu opóźnionego lub wyprzedzonego. W celu zapewnienia istnienia przynajmniej trzech dodatnich rozwiązań wykorzystano twierdzenie Avery-Petersona.
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Design of Structure of Tension Leg Platform for 6 MW Offshore Wind Turbine Based On Fem Analysis
PublikacjaThe article presents the calculation and design stages of the TLP platform serving as a supporting construction of a 6 MW offshore wind turbine. This platform is designed to anchor at sea at a depth of 60 m. The authors presented the method of parameterization and optimization of the hull geometry. For the two selected geometry variants, the load and motion calculations of the platform subjected to wind, wave and current under...
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Dynamic Data Management Among Multiple Databases for Optimization of Parallel Computations in Heterogeneous HPC Systems
PublikacjaRapid development of diverse computer architectures and hardware accelerators caused that designing parallel systems faces new problems resulting from their heterogeneity. Our implementation of a parallel system called KernelHive allows to efficiently run applications in a heterogeneous environment consisting of multiple collections of nodes with different types of computing devices. The execution engine of the system is open for...
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Neural network training with limited precision and asymmetric exponent
PublikacjaAlong with an extremely increasing number of mobile devices, sensors and other smart utilities, an unprecedented growth of data can be observed in today’s world. In order to address multiple challenges facing the big data domain, machine learning techniques are often leveraged for data analysis, filtering and classification. Wide usage of artificial intelligence with large amounts of data creates growing demand not only for storage...
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W-dominance: Tradeoff-inspired dominance relation for preference-based evolutionary multi-objective optimization
PublikacjaThe 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...