Premium
Adaptive large variable neighborhood search for a multiperiod vehicle and technician routing problem
Author(s) -
Graf Benjamin
Publication year - 2020
Publication title -
networks
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.977
H-Index - 64
eISSN - 1097-0037
pISSN - 0028-3045
DOI - 10.1002/net.21959
Subject(s) - vehicle routing problem , solver , heuristics , variable neighborhood search , computer science , mathematical optimization , scheduling (production processes) , routing (electronic design automation) , limit (mathematics) , decomposition , variable (mathematics) , iterated local search , metaheuristic , local search (optimization) , job shop scheduling , mathematics , computer network , mathematical analysis , ecology , biology
The VeRoLog Solver Challenge 2018–2019 of the EURO working group vehicle 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.