Vehicle routing problem with limited refueling halts using particle swarm optimization with greedy mutation operator
RAIRO - Operations Research - Recherche Opérationnelle, Tome 49 (2015) no. 4, pp. 689-716

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Route planning and goods distribution are a major component of any logistics. Vehicle Routing Problem is a class of problems addressing the issues of logistics. Vehicle Routing Problem with Limited Refueling Halts is introduced in this paper. The objective is to plan a route with an emphasis on the time and cost involved in refueling vehicles. The method is tailored to find optimal routes with minimal halts at the refueling stations. The problem is modeled as a bi objective optimization problem and is solved using particle swarm optimization. A new mutation operator called greedy mutation operator is introduced. Experiments are conducted with available data sets and MATLABR2011a is used for implementation.

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DOI : 10.1051/ro/2014064
Classification : 90B06, 90C27, 90C59
Keywords: Logistics, Vehicle Routing Problem, particle swarm optimization

Poonthalir, Ganesan 1 ; Nadarajan, Rethnaswamy 1 ; Geetha, Shanmugam 2

1 Department of Applied Mathematics and Computational Sciences, PSG College of Technology, 641004 Coimbatore, India.
2 Department of Computer Applications, PSG College of Technology, 641004 Coimbatore, India.
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     author = {Poonthalir, Ganesan and Nadarajan, Rethnaswamy and Geetha, Shanmugam},
     title = {Vehicle routing problem with limited refueling halts using particle swarm optimization with greedy mutation operator},
     journal = {RAIRO - Operations Research - Recherche Op\'erationnelle},
     pages = {689--716},
     publisher = {EDP-Sciences},
     volume = {49},
     number = {4},
     year = {2015},
     doi = {10.1051/ro/2014064},
     zbl = {1322.90011},
     language = {en},
     url = {http://geodesic.mathdoc.fr/articles/10.1051/ro/2014064/}
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Poonthalir, Ganesan; Nadarajan, Rethnaswamy; Geetha, Shanmugam. Vehicle routing problem with limited refueling halts using particle swarm optimization with greedy mutation operator. RAIRO - Operations Research - Recherche Opérationnelle, Tome 49 (2015) no. 4, pp. 689-716. doi: 10.1051/ro/2014064

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