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Improved Genetic Algorithm Research for Route Optimization of Logistic Distribution

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4 Author(s)
Xiao Bin ; Sch. of Comput. Sci., Southwest Pet. Univeristy, Chengdu, China ; Wang Min ; Liu Yanming ; Fang Yu

This paper aims at GA's weakness and shortage of neighborhood search capability, proposed 3-opt based mutation operator, sub-path communicating operator and dynamic switching mutation of dual-point operator. The simulation results illustrate that the neighborhood search capability could be improved by this operator and the relatively steady solution could be gained as well. Hence, the research and modeling have been achieved for the issues of logistic distribution route which is ubiquitous in practical application of distribution central with various vehicles. By applying advanced GA to solve the issues, the simulation result shows that the improved GA is efficient when solving the problems of distributing routes within multiple distribution centrals with multiple vehicle types.

Published in:

Computational and Information Sciences (ICCIS), 2010 International Conference on

Date of Conference:

17-19 Dec. 2010