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An adaptive memory methodology for the vehicle routing problem with simultaneous pick-ups and deliveries

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  • Zachariadis, Emmanouil E.
  • Tarantilis, Christos D.
  • Kiranoudis, Chris T.

Abstract

This paper deals with a routing problem variant which considers customers to simultaneously require delivery and pick-up services. The examined problem is referred to as the Vehicle Routing Problem with Simultaneous Pick-ups and Deliveries (VRPSPD). VRPSPD is an NP-hard combinatorial optimization problem, practical large-scale instances of which cannot be solved by exact solution methodologies within acceptable computational times. Our interest was therefore focused on metaheuristic solution approaches. In specific, we introduce an Adaptive Memory (AM) algorithmic framework which collects and combines promising solution features to generate high-quality solutions. The proposed strategy employs an innovative memory mechanism to systematically maximize the amount of routing information extracted from the AM, in order to drive the search towards diverse regions of the solution space. Our metaheuristic development was tested on numerous VRPSPD instances involving from 50 to 400 customers. It proved to be rather effective and efficient, as it produced high-quality solutions, requiring limited computational effort. Furthermore, it managed to produce several new best solutions.

Suggested Citation

  • Zachariadis, Emmanouil E. & Tarantilis, Christos D. & Kiranoudis, Chris T., 2010. "An adaptive memory methodology for the vehicle routing problem with simultaneous pick-ups and deliveries," European Journal of Operational Research, Elsevier, vol. 202(2), pages 401-411, April.
    • Handle: RePEc:eee:ejores:v:202:y:2010:i:2:p:401-411
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    1. J Privé & J Renaud & F Boctor & G Laporte, 2006. "Solving a vehicle-routing problem arising in soft-drink distribution," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 57(9), pages 1045-1052, September.
    2. J-F Chen & T-H Wu, 2006. "Vehicle routing problem with simultaneous deliveries and pickups," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 57(5), pages 579-587, May.
    3. Marius M. Solomon, 1987. "Algorithms for the Vehicle Routing and Scheduling Problems with Time Window Constraints," Operations Research, INFORMS, vol. 35(2), pages 254-265, April.
    4. G. Clarke & J. W. Wright, 1964. "Scheduling of Vehicles from a Central Depot to a Number of Delivery Points," Operations Research, INFORMS, vol. 12(4), pages 568-581, August.
    5. Gribkovskaia, Irina & Halskau, Oyvind sr. & Laporte, Gilbert & Vlcek, Martin, 2007. "General solutions to the single vehicle routing problem with pickups and deliveries," European Journal of Operational Research, Elsevier, vol. 180(2), pages 568-584, July.
    6. Paolo Toth & Daniele Vigo, 2003. "The Granular Tabu Search and Its Application to the Vehicle-Routing Problem," INFORMS Journal on Computing, INFORMS, vol. 15(4), pages 333-346, November.
    7. S Salhi & G Nagy, 1999. "A cluster insertion heuristic for single and multiple depot vehicle routing problems with backhauling," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 50(10), pages 1034-1042, October.
    8. 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.
    9. Paessens, H., 1988. "The savings algorithm for the vehicle routing problem," European Journal of Operational Research, Elsevier, vol. 34(3), pages 336-344, March.
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    Cited by:

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    4. Pandelis, D.G. & Karamatsoukis, C.C. & Kyriakidis, E.G., 2013. "Finite and infinite-horizon single vehicle routing problems with a predefined customer sequence and pickup and delivery," European Journal of Operational Research, Elsevier, vol. 231(3), pages 577-586.
    5. Shih-Che Lo, 2022. "A Particle Swarm Optimization Approach to Solve the Vehicle Routing Problem with Cross-Docking and Carbon Emissions Reduction in Logistics Management," Logistics, MDPI, vol. 6(3), pages 1-15, September.
    6. Henriette Koch & Andreas Bortfeldt & Gerhard Wäscher, 2018. "A hybrid algorithm for the vehicle routing problem with backhauls, time windows and three-dimensional loading constraints," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 40(4), pages 1029-1075, October.
    7. Huey-Kuo Chen & Huey-Wen Chou & Che-Fu Hsueh & Yen-Ju Yu, 2015. "The paired many-to-many pickup and delivery problem: an application," TOP: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 23(1), pages 220-243, April.
    8. Henriette Koch & Andreas Bortfeldt & Gerhard Wäscher, 2017. "A hybrid solution approach for the 3L-VRP with simultaneous delivery and pickups," FEMM Working Papers 170005, Otto-von-Guericke University Magdeburg, Faculty of Economics and Management.
    9. Kalayci, Can B. & Kulak, Osman & Günther, Hans-Otto, 2015. "A perturbation based variable neighborhood search heuristic for solving the Vehicle Routing Problem with Simultaneous Pickup and Delivery with Time LimitAuthor-Name: Polat, Olcay," European Journal of Operational Research, Elsevier, vol. 242(2), pages 369-382.
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