Route design for last-in,first-out deliveries with backhauling |
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| Affiliation: | 1. Graduate Program in Operations Research & Industrial Engineering, The University of Texas, Austin, TX 78712, United States;2. Department of Decision Sciences, School of Business, The George Washington University, Washington, DC 20052, United States;3. Department of Biomedical, Industrial and Human Factors Engineering, Wright State University, Dayton, OH 45435, United States;1. CNRS and Ceremade, Université Paris-Dauphine, Place du Maréchal De Lattre De Tassigny, 75775 Paris Cedex 16, France;2. Unit of Neuroscience, Information and Complexity, CNRS UPR-3293, 1 Avenue de la Terrasse, 91198 Gif-sur-Yvette, France;1. Service d’explorations fonctionnelles pédiatriques, Hôpital d’enfants, Vandoeuvre, France;2. EA 3450 – Laboratoire de Physiologie, Faculté de Médecine, Université Lorraine, Vandoeuvre, France;1. LUNAM Université, École Centrale de Nantes, IRCCyN UMR CNRS 6597 (Institut de Recherche en Communications et Cybernétique de Nantes), 1 rue de la Noë - B.P. 92101 - 44321 Nantes Cedex 3, France;2. ETH Zürich, Switzerland;3. BISON group, Automatic Control Laboratory, ETH Zürich Physikstrasse 3, 8092 Zurich, Switzerland |
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| Abstract: | ![]()
The retail route design problem extends the capacitated vehicle routing problem with time windows by introducing several operational constraints, including order loading and delivery restrictions (last-in, first-out), order-dependent vehicle capacity, material handling limits at the warehouse, backhauling, and driving time bounds. In this paper, the problem is modeled on a directed network for an application associated with a major grocery chain. Because the corresponding mixed-integer program proved too difficult to solve with commercial software for real instances, we developed a greedy randomized adaptive search procedure (GRASP) augmented with tabu search to provide solutions. Testing was done using data sets provided Kroger, the largest grocery chain in the US, and benchmarked against a previously developed column generation algorithm. The results showed that cost reductions of $4887 per day or 5.58% per day on average, compared to Kroger’s corresponding solutions. |
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| Keywords: | Vehicle routing Pickup and delivery GRASP Tabu search Last-in first-out Grocery stores |
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