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A review of approaches to modeling applied vehicle routing problems

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arxiv 2105.10950 v1 pith:MXRA2IQB submitted 2021-05-23 cs.AI

classification cs.AI
keywords problemsmodelingroutingvehiclealgorithmsapproachescomparisondecisions
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Due to the practical importance of vehicle routing problems (VRP), there exists an ever-growing body of research in algorithms and (meta)heuristics for solving such problems. However, the diversity of VRP domains creates the separate problem of modeling such problems -- describing the domain entities (and, in particular, the planning decisions), the set of valid planning decisions, and the preferences between different plans. In this paper, we review the approaches for modeling vehicle routing problems. To make the comparison more straightforward, we formulate several criteria for evaluating modeling methods reflecting the practical requirements of the development of optimization algorithms for such problems. Finally, as a result of this comparison, we discuss several future research avenues in the field of modeling VRP domains.

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Cited by 1 Pith paper

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. Feasibility-Preserving Quantum Search for Constrained Transportation Routing

    quant-ph 2026-08 reject novelty 4.0 of 10

    A column-wise swap mixer for QAOA-based TSP and VRP is proposed, but its claimed feasibility guarantee is contradicted by the paper's own inter-vehicle swap equations.

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