Hybrid Genetic Search for Dynamic Vehicle Routing with Time Windows

Mohammed Ghannam () and Ambros Gleixner ()
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Mohammed Ghannam: HTW Berlin
Ambros Gleixner: HTW Berlin

Chapter Chapter 35 in Operations Research Proceedings 2023, 2025, pp 273-280 from Springer

Abstract: Abstract The dynamic vehicle routing problem with time windows (DVRPTW) is a generalization of the classical VRPTW to an online setting, where customer data arrives in batches and real-time routing solutions are required. In this paper, we adapt the Hybrid Genetic Search (HGS) algorithm, a successful heuristic for VRPTW, to the dynamic variant. We discuss the affected components of the HGS algorithm including giant-tour representation, cost computation, initial population, crossover, and local search. Our approach modifies these components for DVRPTW, attempting to balance solution quality and constraints on future customer arrivals. To this end, we devise methods for comparing different-sized solutions, normalizing costs, and accounting for future epochs. Though our methods do not require any prior training, computational results on data from the EURO meets NeurIPS Vehicle Routing Competition 2022 demonstrate significantly improved solution quality over the best-performing baseline algorithm.

Keywords: Vehicle routing; Online optimization; Metaheuristics; Genetic algorithms (search for similar items in EconPapers)
Date: 2025
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DOI: 10.1007/978-3-031-58405-3_35

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