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VRP12 (vehicle routing problem with distances one and two) with side constraints

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  • Ceranoglu, Ahmet N.
  • Duman, Ekrem

Abstract

The problem undertaken in this study is inspired from a real life application. Consider a vehicle routing problem where the distances between the customer locations are either one or two. We name this problem as VRP12 in an analogy for the name TSP12 used for the traveling salesman problem in the literature. Additionally, assume that, the time to visit each customer is not constant and the visiting time together with the travel time constitutes the capacity of the vehicle. Furthermore, each customer has two characteristics and any two customers having a common characteristic should not be visited at the same time. If visited, a penalty fee incurs. In this study, we give the formulation of this problem and suggest some simple but effective algorithms that can be used to solve it. The algorithms are built with the relaxation of the side constraints but their performances are evaluated with their success in satisfying them. Information on our case study is also provided.

Suggested Citation

  • Ceranoglu, Ahmet N. & Duman, Ekrem, 2013. "VRP12 (vehicle routing problem with distances one and two) with side constraints," International Journal of Production Economics, Elsevier, vol. 144(2), pages 461-467.
    • Handle: RePEc:eee:proeco:v:144:y:2013:i:2:p:461-467
    DOI: 10.1016/j.ijpe.2013.03.014
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    References listed on IDEAS

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    1. E Duman & M H Ozcelik & A N Ceranoglu, 2005. "A TSP (1,2) application arising in cable assembly shops," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 56(6), pages 642-648, June.
    2. Christos H. Papadimitriou & Mihalis Yannakakis, 1993. "The Traveling Salesman Problem with Distances One and Two," Mathematics of Operations Research, INFORMS, vol. 18(1), pages 1-11, February.
    3. Jin, Mingzhou & Liu, Kai & Bowden, Royce O., 2007. "A two-stage algorithm with valid inequalities for the split delivery vehicle routing problem," International Journal of Production Economics, Elsevier, vol. 105(1), pages 228-242, January.
    4. Nagy, Gabor & Salhi, Said, 2005. "Heuristic algorithms for single and multiple depot vehicle routing problems with pickups and deliveries," European Journal of Operational Research, Elsevier, vol. 162(1), pages 126-141, April.
    5. Laporte, Gilbert, 1992. "The vehicle routing problem: An overview of exact and approximate algorithms," European Journal of Operational Research, Elsevier, vol. 59(3), pages 345-358, June.
    6. Hong, Sung-Chul & Park, Yang-Byung, 1999. "A heuristic for bi-objective vehicle routing with time window constraints," International Journal of Production Economics, Elsevier, vol. 62(3), pages 249-258, September.
    7. Kritikos, Manolis N. & Ioannou, George, 2013. "The heterogeneous fleet vehicle routing problem with overloads and time windows," International Journal of Production Economics, Elsevier, vol. 144(1), pages 68-75.
    8. Wang, Hsiao-Fan & Chen, Ying-Yen, 2013. "A coevolutionary algorithm for the flexible delivery and pickup problem with time windows," International Journal of Production Economics, Elsevier, vol. 141(1), pages 4-13.
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    Cited by:

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    2. Jana, R.K. & Mitra, Subrata K. & Sharma, Dinesh K., 2018. "Software vendors travel management decisions using an elitist nonhomogeneous genetic algorithm," International Journal of Production Economics, Elsevier, vol. 202(C), pages 123-131.
    3. Kuo, Tsai Chi & Chen, Gary Yu-Hsin & Wang, Miao Ling & Ho, Ming Way, 2014. "Carbon footprint inventory route planning and selection of hot spot suppliers," International Journal of Production Economics, Elsevier, vol. 150(C), pages 125-139.

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