Metaheuristic Approaches for Vehicle Routing Problems

M. Saravanan and K.A.Sundararaman
Additional contact information
M. Saravanan: Department of Mechanical Engineering, RVS College of Engineering & Technology, Tamilnadu, India
K.A.Sundararaman: Department of Mechanical Engineering, RVS College of Engineering & Technology, Tamilnadu, India

International Journal of Information Systems and Supply Chain Management (IJISSCM), 2013, vol. 6, issue 2, 17-32

Abstract: Routing of service vehicles are the heart of many service operations. Exclusively vehicle routing problem (VRP) plays a central role in the optimization of distribution networks. The routing of service vehicles has a major impact on the quality of the service provided. In distribution of goods and services, it is time and again required to determine a combination of least cost vehicle routes through a set of geographically scattered customers, subject to side constraints. The case most commonly studied is where all vehicles are identical. Due to the complexity involved in solving the VRP, most researchers concentrate on using meta-heuristics for solving real-life problems. In this paper, heuristic methods based on Ant Colony Optimization and Simulated Annealing algorithms are developed and search strategies are investigated. Computational results are reported on randomly generated problems. These methods significantly improve in minimizing the total distances travelled by the vehicles.

Date: 2013
References: Add references at CitEc
Citations:

Downloads: (external link)
https://services.igi-global.com/resolvedoi/resolve ... 18/jisscm.2013040102 (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:igg:jisscm:v:6:y:2013:i:2:p:17-32

Access Statistics for this article

International Journal of Information Systems and Supply Chain Management (IJISSCM) is currently edited by John Wang

More articles in International Journal of Information Systems and Supply Chain Management (IJISSCM) from IGI Global
Bibliographic data for series maintained by Journal Editor ().