2013Bulletin of Electrical Engineering and InformaticsOpen access

Particle Swarm Optimization in Solving Capacitated Vehicle Routing Problem

Mohamad Tavakoli, Ashkan Sami

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Abstract

The Capacitated Vehicle Routing Problem (CVRP) is an NP-Hard problem, which means it is impossible to find a polynomial time solution for it. So researchers try to reach a near optimum solution by using meta-heuristic algorithms. The aim of CVRP is to find optimum route for every vehicle and a sequence of customers, that vehicle serve. This paper proposes a method on how PSO is adjusted for a discrete space problem like CVRP. The process of tweaking solutions is described in detail. At last for evaluation of proposed approach and show the effectiveness of it, the result of running proposed approach over benchmarking data set of capacitated vehicle routing problem is illustrated.

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What this paper is about

The Capacitated Vehicle Routing Problem (CVRP) is an NP-Hard problem, which means it is impossible to find a polynomial time solution for it. So researchers try to reach a near optimum solution by using meta-heuristic algorithms. The aim of CVRP is to find optimum route for every vehicle and a sequence of customers, that vehicle serve. This paper proposes a method on how PSO is adjusted for a discrete space problem like CVRP. The process of tweaking solutions is described in detail. At last for evaluation of proposed approach and show the effectiveness of it, the result of running proposed approach over benchmarking data set of capacitated vehicle routing problem is illustrated.

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Available abstract

The Capacitated Vehicle Routing Problem (CVRP) is an NP-Hard problem, which means it is impossible to find a polynomial time solution for it. So researchers try to reach a near optimum solution by using meta-heuristic algorithms. The aim of CVRP is to find optimum route for every vehicle and a sequence of customers, that vehicle serve. This paper proposes a method on how PSO is adjusted for a discrete space problem like CVRP. The process of tweaking solutions is described in detail. At last for evaluation of proposed approach and show the effectiveness of it, the result of running proposed approach over benchmarking data set of capacitated vehicle routing problem is illustrated.

Key concepts: Vehicle routing problem, Particle swarm optimization, Heuristic, Mathematical optimization, Set (abstract data type), Routing (electronic design automation), Computer science, Process (computing)

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