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An Adaptive Large Neighborhood Search for the Location-routing Problem with Intra-route Facilities

Author

Listed:
  • Maximilian Schiffer

    (Chair of Operations Management, School of Business and Economics, RWTH Aachen University, 52072 Aachen, Germany)

  • Grit Walther

    (Chair of Operations Management, School of Business and Economics, RWTH Aachen University, 52072 Aachen, Germany)

Abstract

Recent research on location-routing problems has been focusing on locating facilities as the starting and end point of routes. In this paper, we investigate a new type of location-routing problem. In the location-routing problem with intra-route facilities, the location of depots is known, whereas the location of facilities for intermediate stops has to be determined to keep vehicles operational. We present an adaptive large neighborhood search which is enhanced by local search and dynamic programming components, and derive new penalty functions for time-efficient neighborhood evaluation. We show that this algorithm is suitable for solving various problems with intra-route facilities by deriving new best known solutions for the recently published electric location-routing problem with time windows and partial recharging, as well as for the battery swap station electric vehicle location-routing problem. Additionally, we create new real-world benchmark instances and show results as well. Furthermore, we assess the competitiveness of our algorithm on the electric vehicle routing problem with time windows for full and partial recharging, and derive new best known solutions for both problem variants.

Suggested Citation

  • Maximilian Schiffer & Grit Walther, 2018. "An Adaptive Large Neighborhood Search for the Location-routing Problem with Intra-route Facilities," Transportation Science, INFORMS, vol. 52(2), pages 331-352, March.
    • Handle: RePEc:inm:ortrsc:v:52:y:2018:i:2:p:331-352
    DOI: 10.1287/trsc.2017.0746
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    References listed on IDEAS

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