Local search metaheuristics for Capacitated Vehicle Routing Problem: a comparative study

• Main Authors: Sergey Mikchailovitch Avdochin, Ekaterina Nikolaevna Beresneva
• Format: Article
• Language: English
• Published: Ivannikov Institute for System Programming of the Russian Academy of Sciences 2019-10-01
• Series: Труды Института системного программирования РАН
• Subjects: задача маршрутизации с ограничением по грузоподъемности; локально-оптимальные метаэвристики; lkh-3; алгоритм переменного перемещения: метод отжига; алгоритм управляемого поиска; алгоритм поиска с запретами
• Online Access: https://ispranproceedings.elpub.ru/jour/article/view/1199

This study is concerned with local search metaheuristics for solving Capacitated Vehicle Routing Problem (CVRP). In this problem the optimal design of routes for a fleet of vehicles with a limited capacity to serve a set of customers must be found. The problem is NP-hard, therefore heuristic algorithms which provide near-optimal polynomial-time solutions are still actual. This experimental analysis is a continue of previous research on construction heuristics for CVRP. It was investigated before that Clarke and Wright Savings (CWS) heuristic is the best among constructive algorithms except for a few instances with geometric type of clients’ distribution where Nearest Neighbor (NN) heuristic is better. The aim of this work is to make a comparison of best-known local search metaheuristics by criteria of error rate and running time with CWS or NN as initial algorithms because there were not found any such state-of-the-art comparative study. An experimental comparison is made using 8 datasets from well-known library because it is interesting to analyze “effectiveness” of algorithms depending on type of input data. Overall, five different groups of Pareto optimal algorithms are defined and described.