Mathematical model and genetic algorithm for distribution logistics problem with maximum route length

P. Sivakumar, K. Ganesh and S. Arunachalam

International Journal of Logistics Economics and Globalisation, 2008, vol. 1, issue 3/4, 307-329

Abstract: Logistics is no longer seen as tactical and cost-driven – it is strategic. Considering the driver-on-time rules and with the perishable nature of the products, the travel length/time is one of the critical constraints in distribution logistics. We consider a typical logistics problem with maximum route length constraint. The variant is termed as simultaneous delivery and pick-up with maximum route length (SDPM). We developed a unified mixed-integer-linear programming (MILP) model and genetic algorithm to solve SDPM and the standard variant, vehicle routing problem with simultaneous delivery and pick-up (VRPSDP). Benchmark datasets for VRPSDP and randomly generated datasets for SDPM are solved using MILP model and genetic algorithm and the results are compared with best-known solution. The results of genetic algorithm are encouraging.

Keywords: distribution logistics; genetic algorithms; GAs; maximum route length; MILP; mixed integer linear programming; VRPSDP; vehicle routing problem; simultaneous delivery; simultaneous pick-up; mathematical modelling. (search for similar items in EconPapers)
Date: 2008
References: Add references at CitEc
Citations:

Downloads: (external link)
http://www.inderscience.com/link.php?id=23164 (text/html)
Access to full text is restricted to subscribers.

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:ids:injleg:v:1:y:2008:i:3/4:p:307-329

Access Statistics for this article

More articles in International Journal of Logistics Economics and Globalisation from Inderscience Enterprises Ltd
Bibliographic data for series maintained by Sarah Parker ().