Enhanced Multi-Strategy Particle Swarm Optimization for Constrained Problems with an Evolutionary-Strategies-Based Unfeasible Local Search Operator

Enhanced Multi-Strategy Particle Swarm Optimization for Constrained Problems with an Evolutionary-Strategies-Based Unfeasible Local Search Operator

Nowadays, optimization problems are solved through meta-heuristic algorithms based on stochastic search approaches borrowed from mimicking natural phenomena. Notwithstanding their successful capability to handle complex problems, the No-Free Lunch Theorem by Wolpert and Macready (1997) states that t...

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Bibliographic Details
Main Authors: Marco Martino Rosso, Raffaele Cucuzza, Angelo Aloisio, Giuseppe Carlo Marano
Format: Article
Language:English
Published: MDPI AG 2022-02-01
Series:Applied Sciences
Subjects:
particle swarm optimization (PSO)
multi-strategy PSO
self-adaptive evolutionary strategies (ES)
local search operator
constraints handling
Online Access:https://www.mdpi.com/2076-3417/12/5/2285

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https://www.mdpi.com/2076-3417/12/5/2285

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