The Fragility-Constrained Vehicle Routing Problem with Time Windows

Clément Altman (), Guy Desaulniers () and Fausto Errico ()
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Clément Altman: Department of Mathematics and Industrial Engineering, Polytechnique Montréal, Montréal, Québec H3T 1J4, Canada; Group for Research in Decision Analysis, Pavillon André Aisenstadt, Montréal, Québec H3T 1J4, Canada
Guy Desaulniers: Department of Mathematics and Industrial Engineering, Polytechnique Montréal, Montréal, Québec H3T 1J4, Canada; Group for Research in Decision Analysis, Pavillon André Aisenstadt, Montréal, Québec H3T 1J4, Canada
Fausto Errico: Group for Research in Decision Analysis, Pavillon André Aisenstadt, Montréal, Québec H3T 1J4, Canada; Department of Civil Engineering, École de Technologie Supérieure de Montréal, Montréal, Québec H3C 1K3, Canada; Interuniversity Research Centre in Enterprise Network, Logistics and Transportation, Pavillon André Aisenstadt, Montréal, Québec H3T 1J4, Canada

Transportation Science, 2023, vol. 57, issue 2, 552-572

Abstract: We study a new variant of the well-studied vehicle routing problem with time windows (VRPTW), called the fragility-constrained VRPTW, which assumes that (1) the capacity of a vehicle is organized in multiple identical stacks; (2) all items picked up at a customer are either “fragile” or not; (3) no nonfragile items can be put on top of a fragile item (the fragility constraint); and (4) no en route load rearrangement is possible. We first characterize the feasibility of a route with respect to this fragility constraint. Then, to solve this new problem, we develop an exact branch-price-and-cut (BPC) algorithm that includes a labeling algorithm exploiting this feasibility characterization to efficiently generate feasible routes. This algorithm is benchmarked against another BPC algorithm that deals with the fragility constraint in the column generation master problem through infeasible path cuts. Our computational results show that the former BPC algorithm clearly outperforms the latter in terms of computational time and that the fragility constraint has a greater impact on the optimal solution cost (compared with that of the VRPTW) when vehicle capacity decreases, stack height increases, and for a more balanced mix of customers with fragile and nonfragile items.

Keywords: vehicle routing; multiple stacks; fragility loading constraint; branch-price-and-cut; route feasibility characterization (search for similar items in EconPapers)
Date: 2023
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Persistent link: https://EconPapers.repec.org/RePEc:inm:ortrsc:v:57:y:2023:i:2:p:552-572

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