The Improvement of Hybrid Particle Swarm Algorithm and its Application

Abstract:

Hybrid multi-objective particle swarm algorithm is applied to vehicle routing problem and achieved good results, this paper based on the previous work, dynamic inertia weight is added to the particle swarm algorithm with intelligence factors, it improved the global search ability and the capacity of local convergence of the particle swarm algorithm; and the idea of immunity is introduced in the algorithm ,which makes the hybrid multi-objective particle swarm algorithm can effectively discard the repeated solutions in solving vehicle routing problems, this operation can improve the efficiency of the algorithm, and obtain better results under the same conditions.

• Periodical: Advanced Materials Research (Volumes 268-270)
• Pages: 798-802
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.268-270.798
• Online since: July 2011
• Authors: Shu Rong Zou, Peng Xin Ding, Hong Wei Zhang
• Keywords: Immunity, Inertia Weight, Multi-Objective, Particle Swarm Algorithm, Vehicle Routing Problem (VRP)

References

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