Multi-objective Evolutionary Algorithms
Multi-Objective Evolutionary Algorithms is a class of population-based stochastic search and optimization algorithms that extend classical evolutionary algorithms by simultaneously optimizing multiple conflicting objectives through mechanisms such as Pareto-based dominance ranking and diversity preservation to approximate the Pareto optimal set.
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Kalyanmoy Deb, Himanshu Jain · IEEE Transactions on Evolutionary Computation · 2013 · 6.8K citations
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Centro de Investigación y de Estudios Avanzados del Instituto Politécnico Nacional, Mexico
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City University of Hong Kong
Hong Kong, Hong Kong
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Southern University of Science and Technology
Shenzhen, China
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Centro de Investigación y de Estudios Avanzados del Instituto Politécnico Nacional
Mexico City, Mexico
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201 publications
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Indian Institute of Technology Kanpur
Kanpur, India
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106 publications
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Xidian University
Xi'an, China
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320 publications
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Nanyang Technological University
Singapore, Singapore
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University of Surrey
Guildford, United Kingdom
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University of Birmingham
Birmingham, United Kingdom
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