BSTBGA: A hybrid genetic algorithm for constrained multi-objective optimization problems

DOI10.1016/j.cor.2012.07.014zbMath1349.90738OpenAlexW2058800751MaRDI QIDQ339580

Gang Du, Xiang Li

Publication date: 11 November 2016

Published in: Computers \& Operations Research (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.cor.2012.07.014

zbMATH Keywords

multi-objective optimizationgenetic algorithmsinequality constraintPareto frontPareto setPareto optimumatrie-treebinary search methodboundary simulation methodconstrained multi-objective optimizationconstraint handlingpopulation diversityrtrie-treetrie-tree

Mathematics Subject Classification ID

Multi-objective and goal programming (90C29) Approximation methods and heuristics in mathematical programming (90C59)

Related Items (2)

A comparative study on multiobjective metaheuristics for solving constrained in-core fuel management optimisation problems ⋮ Constrained optimization for stratified treatment rules with multiple responses of survival data

Uses Software

• DEMORS
• MOEA/D
• SPEA2

Cites Work

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• Inequality constraint handling in genetic algorithms using a boundary simulation method
• Representation and management of MOEA populations based on graphs
• Evolutionary Multi-Criterion Optimization
• Multi-objective meta-heuristics: An overview of the current state-of-the-art

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