Applications of Multiple Objective Genetic Algorithms in the Optimization Design of Tracked Self-Moving Power’s Layout

Abstract:

A multi-objective genetic algorithm is applied into the layout optimization of tracked self-moving power. The layout optimization mathematical model was set up. Then introduced the basic principles of NSGA-Ⅱ, which is a Pareto multi-objective optimization algorithm. Finally, NSGA-Ⅱwas presented to solve the layout problem. The algorithm was proved to be effective by some practical examples. The results showed that the algorithm can spread toward the whole Pareto front, and provide many reasonable solutions once for all.

• Periodical: Applied Mechanics and Materials (Volume 307)
• Pages: 161-165
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.307.161
• Online since: February 2013
• Authors: Hai Jin, Jin Fa Xie
• Keywords: Layout Optimization, Multi-Objective Optimization (MOP), NSGA-II, Pareto Front, Self-Moving Power

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