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Critical Comparison of Multi-objective Optimization Methods: Genetic Algorithms versus Swarm Intelligence
Vladimir Sedenka,Zbynek Raida +1 more
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The paper deals with efficiency comparison of two global evolutionary optimization methods implemented in MATLAB and an elitist Non-dominated Sorting Genetic Algorithm and a novel multi-objective Particle Swarm Optimization (PSO).Abstract:
The paper deals with efficiency comparison of two global evolutionary optimization methods implemented in MATLAB. Attention is turned to an elitist Non-dominated Sorting Genetic Algorithm (NSGA-II) and a novel multi-objective Particle Swarm Optimization (PSO). The performance of optimizers is compared on three different test functions and on a cavity resonator synthesis. The microwave resonator is modeled using the Finite Element Method (FEM). The hit rate and the quality of the Pareto front distribution are classified.read more
Citations
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Finite elements for electrical engineers: Curvilinear, vectorial and unbounded elements
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Maintenance applications of multi-criteria optimization: A review
Chanan S. Syan,Geeta Ramsoobag +1 more
TL;DR: A review of multi criteria models applied for solving maintenance optimization problems and a generalized decision making process for addressing MCO problems is developed to assist researchers and practitioners in considering advanced MCO approaches.
Journal ArticleDOI
GALE: Geometric Active Learning for Search-Based Software Engineering
TL;DR: GALE is a near-linear time MOEA that builds a piecewise approximation to the surface of best solutions along the Pareto frontier that finds comparable solutions to standard methods using far fewer evaluations.
A Novel Multi-Objective Self-Organizing Migrating Algorithm
Zbynek Raida,Petr Kadlec +1 more
TL;DR: A novel stochastic Multi-Objective Self-Organizing Migrating Algorithm (MOSOMA) is introduced that employs a migration technique used in a single-objective Self Organizing Migrate Algorithm to obtain a uniform distribution of Pareto optimal solutions.
Book ChapterDOI
Preference Vector Ant Colony System for Minimising Make-span and Energy Consumption in a Hybrid Flow Shop
TL;DR: A multi-objective scheduling problem in a hybrid flow shop to minimise make-span and energy consumption is discussed and the experimental results show that PVACS outperforms the other two algorithms.
References
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Journal ArticleDOI
A fast and elitist multiobjective genetic algorithm: NSGA-II
TL;DR: This paper suggests a non-dominated sorting-based MOEA, called NSGA-II (Non-dominated Sorting Genetic Algorithm II), which alleviates all of the above three difficulties, and modify the definition of dominance in order to solve constrained multi-objective problems efficiently.
Proceedings ArticleDOI
Particle swarm optimization
TL;DR: A concept for the optimization of nonlinear functions using particle swarm methodology is introduced, and the evolution of several paradigms is outlined, and an implementation of one of the paradigm is discussed.
Journal ArticleDOI
Particle swarm optimization
TL;DR: A snapshot of particle swarming from the authors’ perspective, including variations in the algorithm, current and ongoing research, applications and open problems, is included.
Book
Multi-Objective Optimization Using Evolutionary Algorithms
Kalyanmoy Deb,Deb Kalyanmoy +1 more
TL;DR: This text provides an excellent introduction to the use of evolutionary algorithms in multi-objective optimization, allowing use as a graduate course text or for self-study.
Journal ArticleDOI
Comparison of Multiobjective Evolutionary Algorithms: Empirical Results
TL;DR: This paper provides a systematic comparison of various evolutionary approaches to multiobjective optimization using six carefully chosen test functions and shows that elitism is shown to be an important factor for improving evolutionary multiobjectives search.
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