Hybrid fruit fly optimisation algorithm for field service scheduling problem

Bin Wu, Jing Cheng, Min Dong

Research output: Contribution to journalArticlepeer-review

4 Scopus citations

Abstract

The field service scheduling problem model considering the skill level of workers based on the optimisation goals of travel time, service time, and waiting time is present in the paper. A hybrid fruit fly optimisation algorithm (FOA) is proposed to optimise the model. Based on the features of the problem and merit of the algorithm, a matrix encoding method is designed. Three search operators are then proposed, and the smell-based search strategy and vision-based search strategy for the FOA are redesigned. Additionally, an initialisation operator and a post-optimisation process are constructed to improve the performance of the FOA. Finally, the proposed operators and strategies are compared and analysed, and the hybrid FOA is compared with other algorithms through simulation experiments. The simulation results demonstrate that the proposed hybrid fruit fly optimisation algorithm is an effective method to solve the field service scheduling problem.

Original languageEnglish
Pages (from-to)554-570
Number of pages17
JournalInternational Journal of Automation and Control
Volume14
Issue number5-6
DOIs
StatePublished - 2020

Keywords

  • FSSP
  • Field service scheduling problem
  • Fruit fly optimisation algorithm
  • Intelligent computing

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