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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 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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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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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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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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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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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...