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Modified savings heuristics and genetic algorithm for bi-objective vehicle routing problem with forced backhauls

Publication Type : Journal Article

Publisher : Expert Systems with Applications

Source : Expert Systems with Applications, Volume 39, Number 3, p.2296-2305 (2012)

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Keywords : Automated teller machines, Automatic teller machines, Bank industry, Bi-objective vehicle routing problem with forced backhauls, Costs, Data sets, Distribution costs, Distribution logistics, Genetic algorithms, Modified savings heuristics, Network routing, Routing algorithms, Travel tours, Vehicle Routing Problems, Vehicles

Campus : Coimbatore

School : School of Engineering

Department : Mechanical Engineering

Verified : Yes

Year : 2012

Abstract : The cost of distribution and logistics accounts for a sizable part of the total operating cost of a company. However, the cost associated with operating vehicles and crews for delivery purposes form an important component of total distribution costs. Small percentage saving in these expenses could result in a large amount of savings over a number of years. Increase in the number of automated teller machines (ATMs) in the bank industry enforced the researchers to concentrate much on the optimization of distribution logistics problem. The process of replenishing money in the ATMs is considered as a scope with bi-objectives such as minimizing total routing cost and minimizing the span of travel tour. Some of the pick-up routes of the problem are forced and it is termed as forced backhauls. This problem is termed as bi-objective vehicle routing problems with forced backhauls (BVFB). We developed three heuristics to solve BVFB. Two heuristics are modified savings heuristics and the third heuristic is based on adapted genetic algorithm (GA). Standard data sets of VRPB of real life cases for BVFB and randomly generated datasets for BVFB are solved using all the three heuristics. The results are compared and found that all the three heuristics are competitive in solving BVFB. GA yields better solution compared to the other two heuristics. © 2011 Elsevier Ltd. All rights reserved.

Cite this Research Publication : Dr. Anbuudayasankar S. P., K. Ganesh, S. C. Lenny Koh, and Yves Ducq, “Modified savings heuristics and genetic algorithm for bi-objective vehicle routing problem with forced backhauls”, Expert Systems with Applications, vol. 39, pp. 2296-2305, 2012.

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