Hybrid iterated local search algorithm for optimization route of airplane travel plans

Ahmad Muklason*, I. Gusti Agung Premananda

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

2 Citations (Scopus)


The traveling salesman problem (TSP) is a very popular combinatorics problem. This problem has been widely applied to various real problems. The TSP problem has been classified as a Non-deterministic Polynomial Hard (NP-Hard), so a non-deterministic algorithm is needed to solve this problem. However, a non-deterministic algorithm can only produce a fairly good solution but does not guarantee an optimal solution. Therefore, there are still opportunities to develop new algorithms with better optimization results. This research develops a new algorithm by hybridizing three local search algorithms, namely, iterated local search (ILS) with simulated annealing (SA) and hill climbing (HC), to get a better optimization result. This algorithm aimed to solve TSP problems in the transportation sector, using a case study from the Traveling Salesman Challenge 2.0 (TSC 2.0). The test results show that the developed algorithm can optimize better by 15.7% on average and 11.4% based on the best results compared to previous studies using the Tabu-SA algorithm.

Original languageEnglish
Pages (from-to)4700-4707
Number of pages8
JournalInternational Journal of Electrical and Computer Engineering
Issue number4
Publication statusPublished - Aug 2023


  • Hyper-heuristic
  • Iterated local search
  • Simulated annealing
  • Traveling Salesman Challenge 2.0
  • Traveling salesman problem


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