An efficient evolutionary metaheuristic for the traveling repairman (Minimum latency) problem

Boldizsár Tüű-Szabó, Péter Földesi, László T. Kóczy

Research output: Contribution to journalArticle


In this paper we revisit the memetic evolutionary family of metaheuristics, called Discrete Bacterial Memetic Evolutionary Algorithm (DBMEA), whose members combine Furuhashi’s Bacterial Evolutionary Algorithm and various discrete local search techniques. These algorithms have proven to be efficient approaches for the solution of NP-hard discrete optimization problems such as the Traveling Salesman Problem (TSP) with Time Windows. This paper presents our results in solving the Traveling Repairman Problem (also called Minimum Latency Problem) with a DBMEA variant. The results are compared with state-of-the-art heuristics found in the literature. The DBMEA in most cases turned out to be faster than all other methods, and for the bigger benchmark instances it was also found to have better solutions than the former best-known results. Based on these test results we claim to have found the best approach and thus we suggest the use of the DBMEA for the Traveling Repairman Problem, especially for large instances.

Original languageEnglish
Pages (from-to)781-793
Number of pages13
JournalInternational Journal of Computational Intelligence Systems
Issue number1
Publication statusPublished - 2020

ASJC Scopus subject areas

  • Computer Science(all)
  • Computational Mathematics

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