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Search results for: PARETO FRONT INTERPOLATION
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Constrained multi-objective optimization of compact microwave circuits by design triangulation and pareto front interpolation
PublicationDevelopment of microwave components is an inherently multi-objective task. This is especially pertinent to the design closure stage, i.e., final adjustment of geometry and/or material parameters carried out to improve the electrical performance of the system. The design goals are often conflicting so that the improvement of one normally leads to a degradation of others. Compact microwave passives constitute a representative case:...
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Rapid multi-objective design optimization of miniaturized impedance transformer by Pareto front exploration
PublicationFast multi-objective optimization of compact impedance transformer is discussed. A set of alternative designs representing possible trade-offs between conflicting design criteria, i.e., electrical performance (here, wideband matching) and the structure size, is obtained through Pareto front exploration by means of surrogate-assisted methods.
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Low-cost multi-objective optimization of antennas using Pareto front exploration and response features
PublicationIn the paper, a procedure for low-cost multi-objective optimization of antenna structures is presented. Our approach is based on exploration of the Pareto front representing the best possible trade-offs between conflicting objectives, here, the structure size and its electrical performance. Starting from the design representing the best in-band reflection level, subsequent Pareto-optimal designs are identified through local constrained...
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On Fast Multi-objective Optimization of Antenna Structures Using Pareto Front Triangulation and Inverse Surrogates
PublicationDesign of contemporary antenna systems is a challenging endeavor, where conceptual developments and initial parametric studies, interleaved with topology evolution, are followed by a meticulous adjustment of the structure dimensions. The latter is necessary to boost the antenna performance as much as possible, and often requires handling several and often conflicting objectives, pertinent to both electrical and field properties...
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Rapid Multi-Criterial Antenna Optimization by Means of Pareto Front Triangulation and Interpolative Design Predictors
PublicationModern antenna systems are designed to meet stringent performance requirements pertinent to both their electrical and field properties. The objectives typically stay in conflict with each other. As the simultaneous improvement of all performance parameters is rarely possible, compromise solutions have to be sought. The most comprehensive information about available design trade-offs can be obtained through multi-objective optimization...
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Rapid multi-objective design of integrated on-chip inductors by means of Pareto front exploration and design extrapolation
PublicationIdentification of the best trade-offs between conflicting design objectives allows for making educated design decisions as well as assessing suitability of a given component or circuit for a specific application. In case of inductors, the typical objectives include maximization of the quality factor and minimization of the layout area, as well as maintaining a required inductance at a given operating frequency. This work demonstrates...
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Multi-objective optimization of compact UWB impedance matching transformers using Pareto front exploration and adjoint sensitivities
PublicationIn this paper, a technique for fast multi-objective optimization of impedance matching transformers has been presented. In our approach, a set of alternative designs that represent the best possible trade-offs between conflicting objectives (here, the maximum reflection level within a frequency band of interest and the circuit size) is identified by directly exploring the Pareto front. More specifically, the subsequent Pareto-optimal...
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Recent advances in rapid multiobjective optimization of expensive simulation models in microwave and antenna engineering by Pareto front exploration
PublicationPractical 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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EM-Driven Size Reduction and Multi-Criterial Optimization of Broadband Circularly-Polarized Antennas Using Pareto Front Traversing and Design Extrapolation
PublicationMaintaining small size has become an important consideration in the design of contemporary antenna structures. In the case of broadband circularly polarized (CP) antennas, miniaturization is a challenging process due to the necessity of simultaneous handling of electrical and field properties (reflection, axial ratio, gain), as well as ensuring sufficient frequency range of operation, especially at the lower edge of the antenna...
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Expedite EM-driven generation of Pareto-optimal trade-off curves for variable-turn on-chip inductors
PublicationThis work presents a novel approach to computationally efficient Pareto front identification for variable-turn on-chip inductors. The final outcome is a set of solutions that correspond to the best trade-offs between conflicting design objectives. Here, we consider minimising inductor area and, simultaneously, maximising its quality factor, while maintaining a specified inductance value at a given operating frequency. As opposed...
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Fast Multi-Objective Antenna Design Through Variable-Fidelity EM Simulations
PublicationA technique for fast multi-objective antenna optimization is introduced. A kriging interpolation surrogate constructed from sampled coarse-mesh EM simulations is utilized by multi-objective evolutionary algorithm (MOEA) to obtain the initial Pareto front approximation. The surrogate is defined in a subset of the original design space, determined by means of independently optimized individual objectives. Response correction techniques...
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Multiobjective Aerodynamic Optimization by Variable-Fidelity Models and Response Surface Surrogates
PublicationA computationally efficient procedure for multiobjective design optimization with variable-fidelity models and response surface surrogates is presented. The proposed approach uses the multiobjective evolutionary algorithm that works with a fast surrogate model, obtained with kriging interpolation of the low-fidelity model data enhanced by space-mapping correction exploiting a few high-fidelity training points. The initial Pareto...
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Multi-fidelity EM simulations and constrained surrogate modelling for low-cost multi-objective design optimisation of antennas
PublicationIn this study, a technique for low-cost multi-objective design optimisation of antenna structures has been proposed. The proposed approach is an enhancement of a recently reported surrogate-assisted technique exploiting variable-fidelity electromagnetic (EM) simulations and auxiliary kriging interpolation surrogate, the latter utilised to produce the initial approximation of the Pareto set. A bottleneck of the procedure for higher-dimensional...
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Rapid multi-objective antenna design using point-by-point Pareto set identification and local surrogate models
PublicationAntenna design is inherently a multicriterial problem.Determination of the best possible tradeoffs between conflicting objectives (a so-called Pareto front), such as reflection response, gain, and antenna size, is indispensable from the designer’s point of view, yet challenging when high-fidelity electromagnetic (EM) simulations are utilized for performance evaluation. Here, a novel and computationally...
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EM-Driven Multi-Objective Design of Impedance Transformers By Pareto Ranking Bisection Algorithm
PublicationIn the paper, the problem of fast multi-objective optimization of compact impedance matching transformers is addressed by utilizing a novel Pareto ranking bisection algorithm. It approximates the Pareto front by dividing line segments connecting the designs found in the previous iterations, and refining the obtained candidate solutions by means of poll-type search involving Pareto ranking. The final Pareto set is obtained using...
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Pareto Ranking Bisection Algorithm for Expedited Multi-Objective Optimization of Antenna Structures
PublicationThe purpose of this letter is introduction of a novel methodology for expedited multi-objective design of antenna structures. The key component of the presented approach is fast identification of the initial representation of the Pareto front (i.e., a set of design representing the best possible trade-offs between conflicting objectives) using a Pareto-ranking bisection algorithm. The algorithm finds a discrete set of Pareto-optimal...
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Design space reduction and variable-fidelity EM simulations for feasible Pareto optimization of antennas
PublicationA computationally efficient procedure for multi-objective optimization of antenna structures is presented. In our approach, a response surface approximation (RSA) model created from sampled coarse-discretization EM antenna simulations is utilized to yield an initial set of Pareto-optimal designs using a multi-objective evolutionary algorithm. The final Pareto front representation for the high-fidelity model is obtained using surrogate-based...
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Pareto Ranking Bisection Algorithm for EM-Driven Multi-Objective Design of Antennas in Highly-Dimensional Parameter Spaces
PublicationA deterministic technique for fast surrogate-assisted multi-objective design optimization of antennas in highly-dimensional parameters spaces has been discussed. In this two-stage approach, the initial approximation of the Pareto set representing the best compromise between conflicting objectives is obtained using a bisection algorithm which finds new Pareto-optimal designs by dividing the line segments interconnecting previously...
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Low-Cost Multi-Objective Optimization of Antennas By Means Of Generalized Pareto Ranking Bisection Algorithm
PublicationThis paper introduces a generalized Pareto ranking bisection algorithm for low-cost multi-objective design optimization of antenna structures. The algorithm allows for identifying a set of Pareto optimal sets of parameters (that represent the best trade-offs between considered objectives) by iterative partitioning of the intervals connecting previously found designs and executing a Pareto-ranking-based poll search. The initial...
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Fast Multi-Objective Aerodynamic Optimization Using Sequential Domain Patching and Multifidelity Models
PublicationExploration 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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Generalized Pareto ranking bisection for computationally feasible multi-objective antenna optimization
PublicationMulti-objective optimization (MO) allows for obtaining comprehensive information about possible design trade-offs of a given antenna structure. Yet, executing MO using the most popular class of techniques, population-based metaheuristics, may be computationally prohibitive when full-wave EM analysis is utilized for antenna evaluation. In this work, a low-cost and fully deterministic MO methodology is introduced. The proposed generalized...
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On deterministic procedures for low-cost multi-objective design optimization of miniaturized impedance matching transformers
PublicationPurpose This paper aims to investigate deterministic strategies for low-cost multi-objective design optimization of compact microwave structures, specifically, impedance matching transformers. The considered methods involve surrogate modeling techniques and variable-fidelity electromagnetic (EM) simulations. In contrary to majority of conventional approaches, they do not rely on population-based metaheuristics, which permit lowering...
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Expedited constrained multi-objective aerodynamic shape optimization by means of physics-based surrogates
PublicationIn the paper, computationally efficient constrained multi-objective design optimization of transonic airfoil profiles is considered. Our methodology focuses on fixed-lift design aimed at finding the best possible trade-offs between the two objectives: minimization of the drag coefficient and maximization of the pitching moment. The algorithm presented here exploits the surrogate-based optimization principle, variable-fidelity computational...
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EM-Driven Multi-Objective Optimization of Antenna Structures in Multi-Dimensional Design Spaces
PublicationFeasible multi-objective optimization of antenna structures is presented. An initial set of Pareto optimal solutions is found using a multi-objective evolutionary algorithm (MOEA) working with a fast surrogate antenna model obtained by kriging interpolation of coarse-discretization EM simulation data. To make the surrogate construction computationally feasible in multi-dimensional design space, the space subset containing non-dominated...
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Multi-fidelity aerodynamic design trade-off exploration using point-by-point Pareto set identification
PublicationAerodynamic design is inherently a multi-objective optimization (MOO) problem. Determining the best possible trade-offs between conflicting aerodynamic objectives can be computationally challenging when carried out directly at the level of high-fidelity computational fluid dynamics simulations. This paper presents a computationally cheap methodology for exploration of aerodynamic design trade-offs. In particular, point-by-point...
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Fast Multi-Objective Antenna Optimization Using Sequential Patching and Variable-Fidelity EM Models
PublicationIn this work, a technique for fast multi-objective design optimization of antenna structures is presented. In our approach, the initial approximation of the Pareto set representing the best possible trade-offs between conflicting design objectives is obtained by means of sequential patching of the design space. The latter is a stencil-based search that aims at creating a path that connects the extreme Pareto-optimal designs (obtained...
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Multi-objective antenna design by means of sequential domain patching
PublicationA simple yet robust methodology for rapid multiobjective design optimization of antenna structures has been presented. The key component of our approach is sequential domain patching of the design space which is a stencil-based search that aims at creating a path that connects the extreme Pareto-optimal designs, obtained by means of single-objective optimization runs. The patching process yields the initial approximation of the...
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Rapid multi-objective design optimisation of compact microwave couplers by means of physics-based surrogates
PublicationThe authors introduce a methodology for fast multi-objective design optimisation of miniaturised microwave couplers. The approach exploits the surrogate-based optimisation paradigm with an underlying low-fidelity model constructed from an equivalent circuit of the structure under consideration, corrected through implicit and frequency space mapping. A fast prediction tool obtained this way is subsequently optimised by a multi-objective...
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Multicriteria Evolutionary Weather Routing Algorithm in Practice
PublicationThe Multicriteria Evolutionary Weather Routing Algorithm (MEWRA) has already been introduced by the author on earlier TransNav 2009 and 2011 conferences with a focus on theoretical application to a hybrid-propulsion or motor-driven ship. This paper addresses the topic of possible practical weather routing applications of MEWRA. In the paper some practical advantages of utilizing Pareto front as a result of multicriteria optimization...
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Multi-objective design optimization of antennas for reflection, size, and gain variability using kriging surrogates and generalized domain segmentation
PublicationCost-efficient multi-objective design optimization of antennas is presented. The framework exploits auxiliary data-driven surrogates, a multi-objective evolutionary algorithm for initial Pareto front identification, response correction techniques for design refinement, as well as generalized domain segmentation. The purpose of this last mechanism is to reduce the volume of the design space region that needs to be sampled in order...
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Multi-objective optimization of microwave couplers using corrected domain patching
PublicationPractical design of microwave components and circuits is a compromise between various, often conflicting objectives. In case of compact structures, the trade-offs are typically concerned with the circuit size and its electrical performance. Comprehensive information about the best possible trade-offs can be obtained by means of multi-objective optimization. In this paper, we propose a computationally efficient technique for identifying...
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Approximate Quality Criteria for Difficult Multi-Objective Optimization Problems
PublicationThis 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
PublicationThis 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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Multi-objective optimization of the cavitation generation unit structure of an advanced rotational hydrodynamic cavitation reactor
PublicationHydrodynamic cavitation (HC) has been widely considered a promising technique for industrial-scale process intensifications. The effectiveness of HC is determined by the performance of hydrodynamic cavitation reactors (HCRs). The advanced rotational HCRs (ARHCRs) proposed recently have shown superior performance in various applications, while the research on the structural optimization is still absent. The present study, for the...
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Multi-objective design optimization of antenna structures using sequential domain patching with automated patch size deter-mination
PublicationIn this paper, a simple yet efficient and reliable technique for fully automated multi-objective design optimization of antenna structures using sequential domain patching (SDP) is discussed. The optimization procedure according to SDP is a two-step process: (i) obtaining the initial set of Pareto-optimal designs representing the best possible trade-offs between considered conflicting objectives, and (ii) Pareto set refinement...
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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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Low-cost multi-objective design of compact microwave structures using domain patching
PublicationA good compromise between size and electrical performance is an important design consideration for compact microwave structures. Comprehensive information about size/performance trade-offs can be obtained through multi-objective optimization. Due to considerable electromagnetic (EM) cross-couplings in highly compressed layouts, the design process has to be conducted at the level of high-fidelity EM analysis which is computationally...
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Domain segmentation for low-cost surrogate-assisted multi-objective design optimisation of antennas
PublicationAbstract: Information regarding the best possible design trade-offs of an antenna structure can be obtained through multiobjective optimisation (MO). Unfortunately, MO is extremely challenging if full-wave electromagnetic (EM) simulation models are used for performance evaluation. Yet, for the majority of contemporary antennas, EM analysis is the only tool that ensures reliability. This study introduces a procedure for accelerated...
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Computationally Efficient Multi-Objective Optimization of and Experimental Validation of Yagi-Uda Antenna
PublicationIn this paper, computationally efficient multi-objective optimization of antenna structures is discussed. As a design case, we consider a multi-parameter planar Yagi-Uda antenna structure, featuring a driven element, three directors, and a feeding structure. Direct optimization of the high-fidelity electromagnetic (EM) antenna model is prohibitive in computational terms. Instead, our design methodology exploits response surface...
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Expedited Simulation-Driven Multi-Objective Design Optimization of Quasi-Isotropic Dielectric Resonator Antenna
PublicationMajority 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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Accelerated multi-objective design optimization of antennas by surrogate modeling and domain segmentation
PublicationMulti-objective optimization yields indispensable information about the best possible design trade-offs of an antenna structure, yet it is challenging if full-wave electromagnetic (EM) analysis is utilized for performance evaluation. The latter is a necessity for majority of contemporary antennas as it is the only way of achieving acceptable modeling accuracy. In this paper, a procedure for accelerated multi-objective design of...
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Accelerated multi-objective design of miniaturized microwave components by means of nested kriging surrogates
PublicationDesign of microwave components is an inherently multiobjective task. Often, the objectives are at least partially conflicting and the designer has to work out a suitable compromise. In practice, generating the best possible trade‐off designs requires multiobjective optimization, which is a computationally demanding task. If the structure of interest is evaluated through full‐wave electromagnetic (EM) analysis, the employment of...
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Modeling and Simulation for Exploring Power/Time Trade-off of Parallel Deep Neural Network Training
PublicationIn the paper we tackle bi-objective execution time and power consumption optimization problem concerning execution of parallel applications. We propose using a discrete-event simulation environment for exploring this power/time trade-off in the form of a Pareto front. The solution is verified by a case study based on a real deep neural network training application for automatic speech recognition. A simulation lasting over 2 hours...
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Multi-objective optimization of expensive electromagnetic simulation models
PublicationVast 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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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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Fast multi-objective optimization of antenna structures by means of data-driven surrogates and dimensionality reduction
PublicationDesign of contemporary antenna structures needs to account for several and often conflicting objectives. These are pertinent to both electrical and field properties of the antenna but also its geometry (e.g., footprint minimization). For practical reasons, especially to facilitate efficient optimization, single-objective formulations are most often employed, through either a priori preference articulation, objective aggregation,...
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Low-cost multi-criterial design optimization of compact microwave passives using constrained surrogates and dimensionality reduction
PublicationDesign of contemporary microwave circuits is a challenging task. Typically, it has to take into account several performance requirements and constraints. The design objectives are often conflicting and their simultaneous improvement may not be possible; instead, compromise solutions are to be sought. Representative examples are miniaturized microwave passives where reduction of the circuit size has a detrimental effect on its electrical...
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Grid Implementation of a Parallel Multiobjective Genetic Algorithm for Optimized Allocation of Chlorination Stations in Drinking Water Distribution Systems: Chojnice Case Study
PublicationSolving multiobjective optimization problems requires suitable algorithms to find a satisfactory approximation of a globally optimal Pareto front. Furthermore, it is a computationally demanding task. In this paper, the grid implementation of a distributed multiobjective genetic algorithm is presented. The distributed version of the algorithm is based on the island algorithm with forgetting island elitism used instead of a genetic...
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Ship weather routing featuring w-MOEA/D and uncertainty handling
PublicationThe paper presents a new version of evolutionary multi-objective weather routing (WR) for ships taking into account uncertainties of weather forecasts in route optimization. The method applies authors’ w-MOEA/D algorithm: MOEA/D framework incorporating Decision Maker’s (DM) preferences by means of w-dominance relation. Owing to this, DM preferences are taken into account throughout optimization, allowing the process to focus on...
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Variable-fidelity CFD models and co-Kriging for expedited multi-objective aerodynamic design optimization
PublicationPurpose – 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,...