A particle swarm optimisation algorithm for the capacitated location-routing problem
Jie Liu and
Voratas Kachitvichyanukul
International Journal of Operational Research, 2015, vol. 24, issue 2, 184-213
Abstract:
This article presents a particle swarm optimisation algorithm for solving a capacitated location routing problem (LRP). Based on the framework of particle swarm optimisation with multiple social learning terms (GLNPSO), a solution representation is designed as a multi-dimensional particle representing depot element and customer element. Each particle is decoded into a solution by using the position of a particle to determine depot location, customer assignment, and route construction. The proposed algorithm is evaluated using a set of benchmark problem instances. The results show that the solution quality is good for large problem instances and a total of nine new best solutions are found. Additional performance indices are also proposed as additional indicators to assess the operational performance of the location selection and route forming decisions.
Keywords: location routing problem; capacitated LRP; PSO; particle swarm optimisation; social learning terms; solution representation; decoding; depot location; customer assignment; route construction. (search for similar items in EconPapers)
Date: 2015
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Persistent link: https://EconPapers.repec.org/RePEc:ids:ijores:v:24:y:2015:i:2:p:184-213
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