Particle Swarm Optimization for the Vehicle Routing Problem with Stochastic Demands

This paper introduces a new hybrid algorithmic approach based on Particle Swarm Optimization (PSO) for successfully solving one of the most popular supply chain management problems, the Vehicle Routing Problem with Stochastic Demands (VRPSD). The VRPSD is a well known NP-hard problem in which a vehicle with finite capacity leaves from the depot with full load and has to serve a set of customers whose demands are known only when the vehicle arrives to them. A number of different variants of the PSO are tested and the one that performs better is used for solving benchmark instances from the literature.

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► We solved the Vehicle Routing Problem with Stochastic Demands.
► We used a hybrid approach based on Particle Swarm Optimization.
► We tested a number of variants of Particle Swarm Optimization.
► We tested the algorithm in a number of benchmark instances.
► We compared the algorithm with Differential Evolution and Genetic Algorithms.