Title: Seru scheduling problems with learning effect and job deterioration during an increasing adjustment period

Authors: Ru Zhang; Zhe Zhang; Xiaoling Song; Xiaofang Zhong; Yong Yin

Addresses: School of Economics and Management, Nanjing University of Science and Technology, Nanjing 210094, China ' School of Economics and Management, Nanjing University of Science and Technology, Nanjing 210094, China ' School of Economics and Management, Nanjing University of Science and Technology, Nanjing 210094, China ' School of Economics and Management, Nanjing University of Science and Technology, Nanjing 210094, China ' Graduate School of Business, Doshisha University, Karasuma-Imadegawa, Kamigyo-ku, Kyoto 602-8580, Japan

Abstract: This paper focuses on seru scheduling problems during an increasing adjustment period considering learning effects and job deteriorations, in which the job's processing time is defined by a function of job position in the processing sequence, adjustment position and effects of learning and deterioration. Each seru has an increasing adjustment period, which means that the later the adjustment, the longer the duration. Moreover, the seru will return to its original state and the deterioration effect will restart from new position after adjustment, yet the learning effect keeps growing. The objectives are to minimise the total seru loads (TSL), the total completion times (TC) and the total absolute deviation in completion times (TADC), respectively. A general exact solution method is proposed and optimal solutions for seru scheduling problems are obtained. The comprehensive experimental analysis is conducted, and the results demonstrate that the proposed method is able to return high-quality solutions for seru scheduling problems.

Keywords: seru scheduling; learning effect; job deterioration; increasing adjustment period; exact solution method.

DOI: 10.1504/IJISE.2024.137956

International Journal of Industrial and Systems Engineering, 2024 Vol.46 No.3, pp.323 - 354

Received: 27 Jun 2022
Accepted: 29 Jun 2022
Published online: 12 Apr 2024 *

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