A REVIEW OF SINGLE AND POPULATION-BASED METAHEURISTIC ALGORITHMS SOLVING MULTI DEPOT VEHICLE ROUTING PROBLEM

Authors

  • Sherylaidah Samsuddin Universiti Teknologi Malaysia
  • Mohd Shahizan Othman Universiti Teknologi Malaysia
  • Lizawati Mi Yusuf Universiti Teknologi Malaysia

Keywords:

Metaheuristic, Multi Depot, MDVRP

Abstract

Multi-Depot Vehicle Routing Problem (MDVRP) arises with rapid development in the logistics and transportation field in recent years. This field, mainly, faces challenges in arranging their fleet efficiently to distribute the goods to customers by minimizing distance and cost. Therefore, the decision maker needs to specify the vehicles to reach the particular depot which, serves the customers with the predetermined capacity. Hence, to solve the stated problems, there is a need to apply metaheuristic methods to get minimal transportation costs. This article reviews on single and population-based metaheuristic methods solving MDVRP from the year 2013 until 2018. The methods discussed were simulated annealing (SA), variable neighborhood search (VNS), ant colony algorithm (ACO), particle swarm optimization (PSO) and genetic algorithm (GA). From the previous works, it can be concluded that the application of population based metaheuristic gives better solutions in solving MDVRPs.

Keywords: Metaheuristic, Multi Depot, MDVRP

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Published

2019-01-16

How to Cite

Samsuddin, S., Othman, M. S., & Yusuf, L. M. (2019). A REVIEW OF SINGLE AND POPULATION-BASED METAHEURISTIC ALGORITHMS SOLVING MULTI DEPOT VEHICLE ROUTING PROBLEM. International Journal of Software Engineering and Computer Systems, 4(2), 80–93. Retrieved from https://journal.ump.edu.my/ijsecs/article/view/1270

Issue

Vol. 4 No. 2 (2018): International Journal of Software Engineering and Computer Systems

Section

Full Length Article