A new metaheuristics for solving vehicle routing problem: Partial Comparison Optimization | Zendy

Antono Adhi | Zendy; Budi Santosa | Zendy; Nurhadi Siswanto | Zendy

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A new metaheuristics for solving vehicle routing problem: Partial Comparison Optimization

Author(s) -

Antono Adhi,

Budi Santosa,

Nurhadi Siswanto

Publication year - 2019

Publication title -

iop conference series materials science and engineering

Language(s) - English

Resource type - Journals

eISSN - 1757-899X

pISSN - 1757-8981

DOI - 10.1088/1757-899x/598/1/012023

Subject(s) - vehicle routing problem , metaheuristic , mathematical optimization , computer science , optimization problem , routing (electronic design automation) , mathematics , combinatorial optimization , algorithm , computer network

Vehicle Routing Problem (VRP) is a problem of selecting shortest route from a depot to serve several nodes by considering transport capacity. In this study, a new metaheuristcs algorithm is proposed to solve VRP in order to achieve optimal solution. This metaheuristics algorithm is Partial Comparison Optimization (PCO). This new optimization algorithm was developed to solve combinatorial optimization problems such as VRP. In this study, PCO was tested to solve the problems that existed in the origin VRP. To prove PCO is a good metaheuristics for solving VRP, several of instances of symmetrical VRP were selected from the VRP library to evaluate its performance. The numerical results obtained from the calculation indicated that the proposed optimization method could achieve results that almost similar with the best-known solutions within a reasonable time calculation. It showed that PCO was a good metaheuristics to solve VRP.

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