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

Annual Conference on Industrial and System Engineering 2019

工业技术（总论）

Adhi, A.^1^2 ; Santosa, B.^1 ; Siswanto, N.^1

Industrial Engineering Department, Institut Teknologi Sepuluh Nopember, Surabaya, Indonesia^1

Industrial Engineering Department, Universitas Stikubank, Semarang, Indonesia^2

关键词: Combinatorial optimization problems;    Meta-heuristics algorithms;    Optimal solutions;    Optimization algorithms;    Optimization method;    Transport capacity;    Vehicle routing problem;    Vehicle Routing Problems;   

Others  :  https://iopscience.iop.org/article/10.1088/1757-899X/598/1/012023/pdf
DOI  :  10.1088/1757-899X/598/1/012023

学科分类：工业工程学

来源: IOP

【 摘 要 】

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.