Study on Hybrid Genetic Simulated Annealing Algorithm for Multi-Vehicle and Multi-Cargo Loading Problem

Abstract:

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This paper studies multi-vehicle and multi-cargo loading problem under the limited loading capacity. Hybrid genetic simulated annealing algorithm is used to get the optimization solution. Firstly, adopt hybrid coding so as to make the problem more succinctly. On the basis of cubage-weight balance algorithm, construct initial solution to improve the feasibility. Adopt the improved non-uniform mutation so as to enhance local search ability of chromosomes. Secondly, through utilizing Boltzmann mechanism of simulated annealing algorithm, control crossover and mutation operation of genetic algorithm, search efficiency so as to improve the solution quality of algorithm. Finally, the example can be shown that the above model and algorithm is effective and can provide for large-scale ideas to solve practical problems.

Info:

Periodical:

Advanced Materials Research (Volumes 171-172)

Edited by:

Zhihua Xu, Gang Shen and Sally Lin

Pages:

167-170

DOI:

10.4028/www.scientific.net/AMR.171-172.167

Citation:

X. B. Wang et al., "Study on Hybrid Genetic Simulated Annealing Algorithm for Multi-Vehicle and Multi-Cargo Loading Problem", Advanced Materials Research, Vols. 171-172, pp. 167-170, 2011

Online since:

December 2010

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Price:

$35.00

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