Multiobjective-based concepts to handle constraints in evolutionary algorithms

This paper presents the main multiobjective optimization concepts that have been used in evolutionary algorithms to handle constraints in global optimization problems. A review of some approaches developed under these concepts is provided. Additionally, a comparison of four representative techniques...

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Main Authors: Mezura-Montes, E., Coello, C.A.
Format: Conference Proceeding
Language:English
Subjects:
Algorithm design and analysis
Benchmark testing
Computer science
Constraint optimization
Evolutionary computation
Linear programming
Vectors
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creator Mezura-Montes, E.
Coello, C.A.
description This paper presents the main multiobjective optimization concepts that have been used in evolutionary algorithms to handle constraints in global optimization problems. A review of some approaches developed under these concepts is provided. Additionally, a comparison of four representative techniques using well-known test functions is shown. Finally, the analysis of the results obtained, based on three main points (quality, consistency and diversity) and some conclusions and future trends are also provided.
doi_str_mv 10.1109/ENC.2003.1232894
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subjects Algorithm design and analysis
Benchmark testing
Computer science
Constraint optimization
Evolutionary computation
Linear programming
Vectors
title Multiobjective-based concepts to handle constraints in evolutionary algorithms
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