Water flow-like algorithm improvement using K-opt local search

Wu Diyi, Zulaiha Ali Othman, Suhaila Zainudin, Ayman Srour

Research output: Contribution to journalArticle

Abstract

The water flow-like algorithm (WFA) is a relatively new metaheuristic algorithm, which has shown good solution for the Travelling Salesman Problem (TSP) and is comparable to state of the art results. The basic WFA for TSP uses a 2-opt searching method to decide a water flow splitting decision. Previous algorithms, such as the Ant Colony System for the TSP, has shown that using k-opt (k>2) improves the solution, but increases its complexity exponentially. Therefore, this paper aims to present the performance of the WFA-TSP using 3-opt and 4-opt, respectively, compare them with the basic WFA-TSP using 2-opt and the state of the art algorithms. The algorithms are evaluated using 16 benchmarks TSP datasets. The experimental results show that the proposed WFA-TSP-4opt outperforms in solution quality compare with others, due to its capacity of more exploration and less convergence.

Original languageEnglish
Pages (from-to)199-210
Number of pages12
JournalPertanika Journal of Science and Technology
Volume25
Issue numberS6
Publication statusPublished - 1 Jun 2017

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Traveling salesman problem
water flow
Water
Benchmarking
Ants
ant

Keywords

  • Combinatorial optimization
  • Nature-inspired metaheuristics
  • Traveling salesman problem
  • Water flow-liked algorithm

ASJC Scopus subject areas

  • Computer Science(all)
  • Chemical Engineering(all)
  • Environmental Science(all)
  • Agricultural and Biological Sciences(all)

Cite this

Water flow-like algorithm improvement using K-opt local search. / Diyi, Wu; Ali Othman, Zulaiha; Zainudin, Suhaila; Srour, Ayman.

In: Pertanika Journal of Science and Technology, Vol. 25, No. S6, 01.06.2017, p. 199-210.

Research output: Contribution to journalArticle

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