Title: A hybrid GA-PSO algorithm for seru scheduling problem with dynamic resource allocation

Authors: Ling Shen; Zhe Zhang; Xiaoling Song; Yong Yin

Addresses: School of Economics and Management, Nanjing University of Science and Technology, Nanjing, China ' School of Economics and Management, Nanjing University of Science and Technology, Nanjing, China ' School of Economics and Management, Nanjing University of Science and Technology, Nanjing, China ' Graduate School of Business, Doshisha University, Karasuma-Imadegawa, Kamigyo-ku, Kyoto, Japan

Abstract: As a new type flexible production mode, seru production is widely used in Japanese enterprises to deal with the manufacturing market with volatile and diversified demand. In practical seru production, product processing time may be related to resource allocation, i.e., more resource allocation, less processing time. Thus, this paper attempts to solve seru scheduling problems with dynamic resource allocation, along with which the learning effect of workers is also considered. A combinatorial optimisation model is proposed to minimise the makespan, and a hybrid GA-PSO algorithm with nonlinear inertia weight is specifically designed to solve the proposed model. Finally, a numerical example is presented to verify the effectiveness of hybrid algorithm. The computational results indicate that hybrid GA-PSO algorithm is efficient, and dynamic resource allocation should be considered in seru scheduling problems. [Submitted 1 February 2021; Accepted 30 April 2021]

Keywords: seru scheduling; GA-PSO; dynamic resource allocation; learning effect.

DOI: 10.1504/IJMR.2023.129301

International Journal of Manufacturing Research, 2023 Vol.18 No.1, pp.100 - 124

Received: 01 Feb 2021
Accepted: 30 Apr 2021
Published online: 06 Mar 2023 *