Island neighboring heuristics harmony search algorithm for flow shop scheduling with blocking

Iyad Abu Doush, Mohammed Azmi Al-Betar, Mohammed A. Awadallah, Zaid Abdi Alkareem Alyasseri, Sharif Naser Makhadmeh, Mohammed El-Abd

Research output: Contribution to journalArticlepeer-review

13 Scopus citations

Abstract

This paper proposes an island neighboring heuristics harmony search algorithm (INHS) to tackle the blocking flow-shop scheduling problem. The island model is used to diversify the population and thus enhance the algorithm performance. The proposed method distributes the individuals in the population into different islands or sub-population. Then the harmony search algorithm iterates to look for and to develop a new solution enhanced by using neighboring heuristics. A migration process is applied, after a predefined number of iterations, to perform an exchange between some individuals in islands. The proposed algorithm is evaluated using 12 real-world datasets, each with 10 instances. A sensitivity analysis of the island model parameters is conducted to choose values that minimize the total flow time. The evaluation is conducted using two criteria, the number of evolutions and the Central Processing Unit (CPU) time using six comparative methods and sixteen comparative methods, respectively. For the first criterion, the proposed algorithm excels other comparative algorithms when solving instances of four datasets. For the second criterion, the proposed algorithm outperforms other comparative methods in six out of the twelve datasets. In conclusion, The obtained results prove the efficiency and competitiveness of the proposed algorithm when tackling the blocking flow-shop scheduling problem.

Original languageEnglish
Article number101127
JournalSwarm and Evolutionary Computation
Volume74
DOIs
StatePublished - Oct 2022

Keywords

  • Flow shop problem
  • Harmony search algorithm
  • Heuristics
  • Island model
  • Optimization
  • Scheduling
  • Structured population

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