A hybrid whale optimization algorithm based on local search strategy for the permutation flow shop scheduling problem

Mohamed Abdel-Basset, Gunasekaran Manogaran, Doaa El-Shahat, Seyedali Mirjalili

Research output: Contribution to journalArticle

82 Citations (Scopus)


The flow shop scheduling problem is one of the most important types of scheduling with a large number of real-world applications. In this paper, we propose a new algorithm that integrates the Whale Optimization Algorithm (WOA) with a local search strategy for tackling the permutation flow shop scheduling problem. The Largest Rank Value (LRV) requires the algorithm to deal with the discrete search space of the problem. The diversity of candidate schedules is improved using a swap mutation operation as well. In addition to the insert-reversed block operation is adopted to escape from the local optima. The proposed hybrid whale algorithm (HWA) is incorporated with Nawaz–Enscore–Ham (NEH) to improve the performance of the algorithm. It is observed that HWA gives competitive results compared to the existing algorithms.

Original languageEnglish
Pages (from-to)129-145
Number of pages17
JournalFuture Generation Computer Systems
Publication statusPublished - 1 Aug 2018
Externally publishedYes



  • Flow shop scheduling
  • Hybrid algorithm
  • Local search
  • Makespan
  • Whale optimization algorithm

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