Multi-objective optimization based on self-adaptive differential evolution algorithm

V. L. Huang; A. K. Qin; Ponnuthurai Nagaratnam Suganthan; M. Fatih Tasgetiren

doi:10.1109/cec.2007.4424939

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Multi-objective optimization based on self-adaptive differential evolution algorithm

V. L. Huang A. K. Qin Ponnuthurai Nagaratnam Suganthan M. Fatih Tasgetiren

Year: 2007 Pages: 3601-3608

DOI: 10.1109/cec.2007.4424939

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Abstract

In this paper, our recently developed Self-adaptive Differential Evolution algorithm (SaDE) is extended to solve numerical optimization problems with multiple conflicting objectives. The performance of the proposed MOSaDE algorithm is evaluated on a suit of 19 benchmark problems provided for the CEC2007 special session (http://www.ntu.edu.sg/home/epnsugan/) on Performance Assessment of Multi-Objective Optimization Algorithms.

Keywords:

Benchmark (surveying) Differential evolution Computer science Algorithm Mathematical optimization Session (web analytics) Optimization problem Evolutionary computation Meta-optimization Differential (mechanical device) Optimization algorithm Mathematics Artificial intelligence Engineering

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Advanced Multi-Objective Optimization Algorithms

Physical Sciences → Computer Science → Computational Theory and Mathematics

Metaheuristic Optimization Algorithms Research

Physical Sciences → Computer Science → Artificial Intelligence

Evolutionary Algorithms and Applications

Physical Sciences → Computer Science → Artificial Intelligence

Multi-objective optimization based on self-adaptive differential evolution algorithm

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