Evolutionary Algorithms in Engineering Design Optimization

Evolutionary algorithms (EAs) are population-based global optimizers, which, due to their characteristics, have allowed us to solve, in a straightforward way, many real world optimization problems in the last three decades, particularly in engineering fields. Their main advantages are the following:...

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Формат:	Online
Язык:	английский
Опубликовано:	MDPI - Multidisciplinary Digital Publishing Institute 2022
Предметы:	Automatic Voltage Regulation system Chaotic optimization Fractional Order Proportional-Integral-Derivative controller Yellow Saddle Goatfish Algorithm two-stage method mono and multi-objective optimization multi-objective optimization optimal design Gough–Stewart parallel manipulator performance metrics diversity control genetic algorithm bankruptcy problem classification T-junctions neural networks finite elements analysis surrogate beam improvements beam T-junctions models artificial neural networks (ANN) limited training data multi-objective decision-making Pareto front preference in multi-objective optimization aeroacoustics trailing-edge noise global optimization evolutionary algorithms nearly optimal solutions archiving strategy evolutionary algorithm non-linear parametric identification multi-objective evolutionary algorithms availability design preventive maintenance scheduling encoding accuracy levels plastics thermoforming sheet thickness distribution evolutionary optimization genetic programming control differential evolution reusable launch vehicle quality control roughness measurement machine vision machine learning parameter optimization distance-based mutation-selection real application experimental study global optimisation worst-case scenario robust min-max optimization optimal control multi-objective optimisation robust design trajectory optimisation uncertainty quantification unscented transformation spaceplanes space systems launchers thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology
Online-ссылка:	ONIX_20220506_9783036527147_155
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Evolutionary Algorithms in Engineering Design Optimization

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