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Heuristics in Vehicle Routing

In: Handbook of Heuristics

Author

Listed:
  • Claudia Archetti

    (University of Brescia, Department of Economics and Management)

  • Kris Braekers

    (Hasselt University, Research Group Logistics)

  • Diego Cattaruzza

    (UMR 9189 – CRIStAL Centre de Recherche an Informatique Signal et Automatique de Lille, Univ. Lille, CNRS, Centrale Lille, Inria
    University of Udine, Department of Mathematics, Computer Science and Physics)

Abstract

Vehicle routing problems are among the most widely studied combinatorial optimization problems. Different classes of routing problems exist which all share a common set of decisions: assigning customers to vehicles and defining the sequence of visit for each vehicle, i.e., determining vehicle routes in order to minimize a given cost function. Problems might differ in the objective function and in the presence of additional constraints. However, routing decisions (plus eventually additional problem-specific decisions) make routing problems extremely challenging. For this reason, the research community has concentrated big efforts on the development of efficient heuristic solution approaches. In this chapter, we first briefly introduce the earliest and most classical heuristic algorithms. Then we concentrate on the most recent developments on heuristics for routing problems, namely, metaheuristics, matheuristics, learning approaches, and heuristics for large-scale problems. We provide reference contributions and discuss the key features of each class of methods, concentrating on the most recent research trends.

Suggested Citation

  • Claudia Archetti & Kris Braekers & Diego Cattaruzza, 2025. "Heuristics in Vehicle Routing," Springer Books, in: Rafael Martí & Panos M. Pardalos & Mauricio G.C. Resende (ed.), Handbook of Heuristics, edition 0, chapter 43, pages 1353-1383, Springer.
  • Handle: RePEc:spr:sprchp:978-3-032-00385-0_65
    DOI: 10.1007/978-3-032-00385-0_65
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