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

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...

Celý popis

Uloženo v:
Podrobná bibliografie
Vydáno v:International journal of electrical and computer engineering (Malacca, Malacca) Ročník 13; číslo 4; s. 4700
Hlavní autoři: Muklason, Ahmad, Agung Premananda, I Gusti
Médium: Journal Article
Jazyk:angličtina
Vydáno: 01.08.2023
ISSN:2088-8708, 2722-2578
On-line přístup:Získat plný text
Tagy: Přidat tag
Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!
Popis
Shrnutí: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.
ISSN:2088-8708
2722-2578
DOI:10.11591/ijece.v13i4.pp4700-4707