A Grid Based Cooperative Co-evolutionary Multi-Objective Algorithm

Authors:
Sepehr Meshkinfam Fard;Ali Hamzeh;Koorush Ziarati
Affiliations:
Department of mathematics, College of Science, Shiraz University, Shiraz, Iran;CSE and IT Department, School of ECE, Shiraz University, Shiraz, Iran;CSE and IT Department, School of ECE, Shiraz University, Shiraz, Iran
Venue:
AICI '09 Proceedings of the International Conference on Artificial Intelligence and Computational Intelligence
Year:
2009

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Abstract

In this paper, a well performing approach in the context of Multi-Objective Evolutionary Algorithm (MOEA) is investigated due to its complexity. This approach called NSCCGA is based on previously introduced approach called NSGA-II. NSCCGA performs better than NSGA-II but with a heavy load of computational complexity. Here, a novel approach called GBCCGA is introduced based on MOCCGA with some modifications. The main difference between GBCCGA and MOCCGA is in their niching technique which instead of the traditional sharing mechanism in MOCCGA, a novel grid-based technique is used in GBCCGA. The reported results show that GBCCGA performs roughly the same as NSCCGA but with very low computational complexity with respect to the original MOCCGA.