Multi-objective optimization using self-adaptive differential evolution algorithm

Authors:
V. L. Huang;S. Z. Zhao;R. Mallipeddi;P. N. Suganthan
Affiliations:
School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore;School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore;School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore;School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore
Venue:
CEC'09 Proceedings of the Eleventh conference on Congress on Evolutionary Computation
Year:
2009

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Abstract

In this paper, we propose a Multiobjective Self-adaptive Differential Evolution algorithm with objective-wise learning strategies (OW-MOSaDE) to solve numerical optimization problems with multiple conflicting objectives. The proposed approach learns suitable crossover parameter values and mutation strategies for each objective separately in a multi-objective optimization problem. The performance of the proposed OW-MOSaDE algorithm is evaluated on a suit of 13 benchmark problems provided for the CEC2009 MOEA Special Session and Competition (http://www3.ntu.edu.sg/home/epnsugan/) on Performance Assessment of Constrained / Bound Constrained Multi-Objective Optimization Algorithms.