A Decomposition Based Evolutionary Algorithm with Angle Penalty Selection Strategy for Many-Objective Optimization

Zhiyong Li; Ke Lin; Mourad Nouioua; Shilong Jiang

doi:10.1007/978-3-319-93815-8_53

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A Decomposition Based Evolutionary Algorithm with Angle Penalty Selection Strategy for Many-Objective Optimization

Zhiyong Li Ke Lin Mourad Nouioua Shilong Jiang

Year: 2018 Lecture notes in computer science Pages: 561-571 Publisher: Springer Science+Business Media

DOI: 10.1007/978-3-319-93815-8_53

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Keywords:

Evolutionary algorithm Mathematical optimization Benchmark (surveying) Population Decomposition Selection (genetic algorithm) Computer science Optimization problem Pareto principle Multi-objective optimization Set (abstract data type) Mathematics Algorithm Artificial intelligence

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Advanced Multi-Objective Optimization Algorithms

Physical Sciences → Computer Science → Computational Theory and Mathematics

Optimal Experimental Design Methods

Social Sciences → Decision Sciences → Management Science and Operations Research

Metaheuristic Optimization Algorithms Research

Physical Sciences → Computer Science → Artificial Intelligence

A Decomposition Based Evolutionary Algorithm with Angle Penalty Selection Strategy for Many-Objective Optimization

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