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

Sherylaidah Samsuddin,Lizawati Mi Yusuf,Mohd Shahizan Othman

doi:10.15282/ijsecs.4.2.2018.6.0050

Sherylaidah Samsuddin, Lizawati Mi Yusuf + Show 1 more

Open Access

https://doi.org/10.15282/ijsecs.4.2.2018.6.0050

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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

Highlights

Nowadays, one of the great challenges due to their high operational costs faced by the distribution companies is to organize their fleet efficiently
This paper presents a review of relevant literature on metaheuristic algorithm focus on single and population-based metaheuristic methods for solving Multi-Depot Vehicle Routing Problem (MDVRP) in recent years
Based on Montoya-Torres (2015), there are 42% of research works on MDVRP using metaheuristic method to solve the problem. 33% used heuristic and 25% used the exact method for recent studies

Summary

INTRODUCTION

One of the great challenges due to their high operational costs faced by the distribution companies is to organize their fleet efficiently. Metaheuristic algorithm is applied for routes construction to get the best result This is because metaheuristic is known as an efficient method to solve many NP-hard problems and it has been proven that metaheuristic can provide excellent quality output within the reasonable time, even for MDVRP (Boussaïd, Lepagnot, & Siarry, 2013). The customer will be assigned in each depot for every route This is to minimize the number of vehicles used and routes, followed by the capacity constraints. A review of single and population-based metaheuristic algorithms solving multi depot vehicle routing problem intractable and time-consuming whereas, in the heuristic method, the capability in the mathematical foundation is not strong enough (Geetha, Vanathi, & Poonthalir, 2012). Most researchers applied metaheuristic methods to solve MDVRPs, further section discusses metaheuristic methods

METAHEURISTICS METHODS

Application of metaheuristic algorithms in MDVRP

Findings

CONCLUSION