IDEAS home Printed from https://ideas.repec.org/a/eee/ejores/v244y2015i1p129-140.html
   My bibliography  Save this article

The k-dissimilar vehicle routing problem

Author

Listed:
  • Talarico, L.
  • Sörensen, K.
  • Springael, J.

Abstract

In this paper we define a new problem, the aim of which is to find a set of k dissimilar solutions for a vehicle routing problem (VRP) on a single instance. This problem has several practical applications in the cash-in-transit sector and in the transportation of hazardous materials. A min–max mathematical formulation is proposed which requires a maximum similarity threshold between VRP solutions, and the number k of dissimilar VRP solutions that need to be generated. An index to measure similarities between VRP solutions is defined based on the edges shared between pairs of alternative solutions. An iterative metaheuristic to generate k dissimilar alternative solutions is also presented. The solution approach is tested using large and medium size benchmark instances for the capacitated vehicle routing problem.

Suggested Citation

  • Talarico, L. & Sörensen, K. & Springael, J., 2015. "The k-dissimilar vehicle routing problem," European Journal of Operational Research, Elsevier, vol. 244(1), pages 129-140.
    • Handle: RePEc:eee:ejores:v:244:y:2015:i:1:p:129-140
    DOI: 10.1016/j.ejor.2015.01.019
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0377221715000399
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.ejor.2015.01.019?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Marshall L. Fisher, 1994. "Optimal Solution of Vehicle Routing Problems Using Minimum K-Trees," Operations Research, INFORMS, vol. 42(4), pages 626-642, August.
    2. Ram Gopalan & Krishna S. Kolluri & Rajan Batta & Mark H. Karwan, 1990. "Modeling Equity of Risk in the Transportation of Hazardous Materials," Operations Research, INFORMS, vol. 38(6), pages 961-973, December.
    3. Jin Y. Yen, 1971. "Finding the K Shortest Loopless Paths in a Network," Management Science, INFORMS, vol. 17(11), pages 712-716, July.
    4. S. Lin & B. W. Kernighan, 1973. "An Effective Heuristic Algorithm for the Traveling-Salesman Problem," Operations Research, INFORMS, vol. 21(2), pages 498-516, April.
    5. Helsgaun, Keld, 2000. "An effective implementation of the Lin-Kernighan traveling salesman heuristic," European Journal of Operational Research, Elsevier, vol. 126(1), pages 106-130, October.
    6. van Leeuwen, P. H. & Volgenant, A., 1983. "Solving symmetric vehicle routing problems asymmetrically," European Journal of Operational Research, Elsevier, vol. 12(4), pages 388-393, April.
    7. TALARICO, Luca & SÖRENSEN, Kenneth & SPRINGAEL, Johan, 2013. "The risk constrained cash-in-transit vehicle routing problem with time windows," Working Papers 2013012, University of Antwerp, Faculty of Business and Economics.
    8. Dell'Olmo, Paolo & Gentili, Monica & Scozzari, Andrea, 2005. "On finding dissimilar Pareto-optimal paths," European Journal of Operational Research, Elsevier, vol. 162(1), pages 70-82, April.
    9. Akgun, Vedat & Erkut, Erhan & Batta, Rajan, 2000. "On finding dissimilar paths," European Journal of Operational Research, Elsevier, vol. 121(2), pages 232-246, March.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Soriano, Adria & Vidal, Thibaut & Gansterer, Margaretha & Doerner, Karl, 2020. "The vehicle routing problem with arrival time diversification on a multigraph," European Journal of Operational Research, Elsevier, vol. 286(2), pages 564-575.
    2. Hoogeboom, Maaike & Dullaert, Wout, 2019. "Vehicle routing with arrival time diversification," European Journal of Operational Research, Elsevier, vol. 275(1), pages 93-107.
    3. Hughes, Michael S. & Lunday, Brian J. & Weir, Jeffrey D. & Hopkinson, Kenneth M., 2021. "The multiple shortest path problem with path deconfliction," European Journal of Operational Research, Elsevier, vol. 292(3), pages 818-829.
    4. Huber, Sandra & Geiger, Martin Josef, 2017. "Order matters – A Variable Neighborhood Search for the Swap-Body Vehicle Routing Problem," European Journal of Operational Research, Elsevier, vol. 263(2), pages 419-445.
    5. Kian, Ramez & Erdoğan, Güneş & de Leeuw, Sander & Sibel Salman, F. & Sabet, Ehsan & Kara, Bahar Y. & Demir, Muhittin H., 2022. "Logistics planning of cash transfer to Syrian refugees in Turkey," European Journal of Operational Research, Elsevier, vol. 296(3), pages 1007-1024.
    6. Zajac, Sandra & Huber, Sandra, 2021. "Objectives and methods in multi-objective routing problems: a survey and classification scheme," European Journal of Operational Research, Elsevier, vol. 290(1), pages 1-25.
    7. Sandra Zajac, 2018. "On a two-phase solution approach for the bi-objective k-dissimilar vehicle routing problem," Journal of Heuristics, Springer, vol. 24(3), pages 515-550, June.
    8. Allahyari, Somayeh & Yaghoubi, Saeed & Van Woensel, Tom, 2021. "A novel risk perspective on location-routing planning: An application in cash transportation," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 150(C).
    9. Zandieh, Fatemeh & Ghannadpour, Seyed Farid, 2023. "A comprehensive risk assessment view on interval type-2 fuzzy controller for a time-dependent HazMat routing problem," European Journal of Operational Research, Elsevier, vol. 305(2), pages 685-707.
    10. Xianlong Ge & Yuanzhi Jin & Long Zhang, 2023. "Genetic-based algorithms for cash-in-transit multi depot vehicle routing problems: economic and environmental optimization," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 25(1), pages 557-586, January.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. TALARICO, Luca & SÖRENSEN, Kenneth & SPRINGAEL, Johan, 2013. "The k-dissimilar vehicle routing problem," Working Papers 2013029, University of Antwerp, Faculty of Business and Economics.
    2. Sandra Zajac, 2018. "On a two-phase solution approach for the bi-objective k-dissimilar vehicle routing problem," Journal of Heuristics, Springer, vol. 24(3), pages 515-550, June.
    3. Pushak, Yasha & Hare, Warren & Lucet, Yves, 2016. "Multiple-path selection for new highway alignments using discrete algorithms," European Journal of Operational Research, Elsevier, vol. 248(2), pages 415-427.
    4. César Rego & Fred Glover, 2010. "Ejection chain and filter-and-fan methods in combinatorial optimization," Annals of Operations Research, Springer, vol. 175(1), pages 77-105, March.
    5. Lucio Bianco & Massimiliano Caramia & Stefano Giordani & Veronica Piccialli, 2016. "A Game-Theoretic Approach for Regulating Hazmat Transportation," Transportation Science, INFORMS, vol. 50(2), pages 424-438, May.
    6. Mohri, Seyed Sina & Mohammadi, Mehrdad & Gendreau, Michel & Pirayesh, Amir & Ghasemaghaei, Ali & Salehi, Vahid, 2022. "Hazardous material transportation problems: A comprehensive overview of models and solution approaches," European Journal of Operational Research, Elsevier, vol. 302(1), pages 1-38.
    7. Ghosh, Diptesh, 2016. "Exploring Lin Kernighan neighborhoods for the indexing problem," IIMA Working Papers WP2016-02-13, Indian Institute of Management Ahmedabad, Research and Publication Department.
    8. Jiang, Zhongzhou & Liu, Jing & Wang, Shuai, 2016. "Traveling salesman problems with PageRank Distance on complex networks reveal community structure," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 463(C), pages 293-302.
    9. Henke, Tino & Speranza, M. Grazia & Wäscher, Gerhard, 2015. "The multi-compartment vehicle routing problem with flexible compartment sizes," European Journal of Operational Research, Elsevier, vol. 246(3), pages 730-743.
    10. Lamb, John D., 2012. "Variable neighbourhood structures for cycle location problems," European Journal of Operational Research, Elsevier, vol. 223(1), pages 15-26.
    11. Escobar, John Willmer & Linfati, Rodrigo & Baldoquin, Maria G. & Toth, Paolo, 2014. "A Granular Variable Tabu Neighborhood Search for the capacitated location-routing problem," Transportation Research Part B: Methodological, Elsevier, vol. 67(C), pages 344-356.
    12. Manerba, Daniele & Mansini, Renata & Riera-Ledesma, Jorge, 2017. "The Traveling Purchaser Problem and its variants," European Journal of Operational Research, Elsevier, vol. 259(1), pages 1-18.
    13. Farasat, Alireza & Nikolaev, Alexander G., 2016. "Signed social structure optimization for shift assignment in the nurse scheduling problem," Socio-Economic Planning Sciences, Elsevier, vol. 56(C), pages 3-13.
    14. Qiu, Yuzhuo & Zhou, Dan & Du, Yanan & Liu, Jie & Pardalos, Panos M. & Qiao, Jun, 2021. "The two-echelon production routing problem with cross-docking satellites," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 147(C).
    15. Gary R. Waissi & Pragya Kaushal, 2020. "A polynomial matrix processing heuristic algorithm for finding high quality feasible solutions for the TSP," OPSEARCH, Springer;Operational Research Society of India, vol. 57(1), pages 73-87, March.
    16. Karapetyan, D. & Gutin, G., 2011. "Lin-Kernighan heuristic adaptations for the generalized traveling salesman problem," European Journal of Operational Research, Elsevier, vol. 208(3), pages 221-232, February.
    17. Luigi Di Puglia Pugliese & Francesca Guerriero, 2016. "On the shortest path problem with negative cost cycles," Computational Optimization and Applications, Springer, vol. 63(2), pages 559-583, March.
    18. Mor, A. & Speranza, M.G. & Viegas, J.M., 2020. "Efficient loading and unloading operations via a booking system," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 141(C).
    19. Rui Xu & Yumiao Huang & Wei Xiao, 2023. "A Two-Level Variable Neighborhood Descent for a Split Delivery Clustered Vehicle Routing Problem with Soft Cluster Conflicts and Customer-Related Costs," Sustainability, MDPI, vol. 15(9), pages 1-22, May.
    20. Chen, Yu-Wang & Zhu, Yao-Jia & Yang, Gen-Ke & Lu, Yong-Zai, 2011. "Improved extremal optimization for the asymmetric traveling salesman problem," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(23), pages 4459-4465.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:ejores:v:244:y:2015:i:1:p:129-140. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/eor .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.