Multi-Objective Chaos Memetic Algorithm for DTLZ Problems

Abstract:

Based on Multi-Objective Memetic Algorithm (MOMA), a novel Multi-Objective Chaos Memetic Algorithm (MOCMA) is proposed . MOCMA is presented to keep population’s diversity, avoid local optimum and improve performance of Multi-Objective Memetic Algorithm. By virtue of the over-spread character of chaos sequence, it is used to generate chromosome to overcome redundancies. At the same time, searching space is enlarged by using sensitivity of chaos initial value. The comparisons of MOCMA with NSGAII in DTLZ problems suggest that MOCMA clearly outperforms in converging towards the true pareto front and finding the spread of solutions.

• Periodical: Advanced Materials Research (Volumes 403-408)
• Pages: 3676-3681
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.403-408.3676
• Online since: November 2011
• Authors: Paranya Ammaruekarat, Phayung Meesad
• Keywords: Chaos Theory, Multi-Objective Memetic Algorithm, Multi-Objective Optimization (MOP)

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