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http://dx.doi.org/10.11627/jkise.2021.44.2.036

Multi-objective Optimization of Vehicle Routing with Resource Repositioning  

Kang, Jae-Goo (Department of Industrial Engineering, Hannam University)
Yim, Dong-Soon (Department of Industrial Engineering, Hannam University)
Publication Information
Journal of Korean Society of Industrial and Systems Engineering / v.44, no.2, 2021 , pp. 36-42 More about this Journal
Abstract
This paper deals with a vehicle routing problem with resource repositioning (VRPRR) which is a variation of well-known vehicle routing problem with pickup and delivery (VRPPD). VRPRR in which static repositioning of public bikes is a representative case, can be defined as a multi-objective optimization problem aiming at minimizing both transportation cost and the amount of unmet demand. To obtain Pareto sets for the problem, famous multi-objective optimization algorithms such as Strength Pareto Evolutionary Algorithm 2 (SPEA2) can be applied. In addition, a linear combination of two objective functions with weights can be exploited to generate Pareto sets. By varying weight values in the combined single objective function, a set of solutions is created. Experiments accomplished with a standard benchmark problem sets show that Variable Neighborhood Search (VNS) applied to solve a number of single objective function outperforms SPEA2. All generated solutions from SPEA2 are completely dominated by a set of VNS solutions. It seems that local optimization technique inherent in VNS makes it possible to generate near optimal solutions for the single objective function. Also, it shows that trade-off between the number of solutions in Pareto set and the computation time should be considered to obtain good solutions effectively in case of linearly combined single objective function.
Keywords
Vehicle Routing Problem with Pickup and Delivery; Static Repositioning of Public Bikes; Multi-Objective Optimization; Strength Pareto Evolutionary Algorithm; Variable Neighborhood Search;
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