Title: Hybrid fruit fly optimisation algorithm for field service scheduling problem

Authors: Bin Wu; Jing Cheng; Min Dong

Addresses: School of Economics and Management, Nanjing Tech University, Nanjing, 211816, China ' School of Economics and Management, Nanjing Tech University, Nanjing, 211816, China ' School of Economics and Management, Nanjing Tech University, Nanjing, 211816, China

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.

Keywords: field service scheduling problem; FSSP; fruit fly optimisation algorithm; intelligent computing.

DOI: 10.1504/IJAAC.2020.110072

International Journal of Automation and Control, 2020 Vol.14 No.5/6, pp.554 - 570

Received: 22 Dec 2018
Accepted: 21 May 2019
Published online: 05 Oct 2020 *

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