Adaptive large variable neighborhood search for a multiperiod vehicle and technician routing problem

Autor(en): Graf, Benjamin
Stichwörter: adaptive large neighborhood search; Computer Science; Computer Science, Hardware & Architecture; LOCAL SEARCH; multiperiod VRP; Operations Research & Management Science; technician routing and scheduling; variable neighborhood descent; VeRoLog Solver Challenge
Erscheinungsdatum: 2020
Herausgeber: WILEY
Volumen: 76
Ausgabe: 2, SI
Startseite: 256
Seitenende: 272
The VeRoLog Solver Challenge 2018-2019 of the EURO working groupvehicle routing and logistics(VeRoLog) considers a multiperiod vehicle and technician routing and scheduling problem. This paper proposes a combination of large neighborhood and local search heuristics and a decomposition approach to efficiently generate competitive solutions under restricted computational resources. The interplay of the heuristics, the decomposition, and the way the search space is explored are orchestrated by an adaptive layer that explicitly considers the instance to be solved, a time limit and the performance of the computing environment. In a computational study it is shown that the method is efficient and effective, especially under tight time restrictions.
ISSN: 00283045
DOI: 10.1002/net.21959

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