Scheduling problem in seru production system considering DeJong’s learning effect and job splitting

Zhe Zhang (), Xiaoling Song (), Huijun Huang (), Yong Yin () and Benjamin Lev ()
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Zhe Zhang: Nanjing University of Science and Technology
Xiaoling Song: Nanjing University of Science and Technology
Huijun Huang: Nanjing University of Science and Technology
Yong Yin: Doshisha University
Benjamin Lev: Drexel University

Annals of Operations Research, 2022, vol. 312, issue 2, No 18, 1119-1141

Abstract: Abstract Seru is a relatively new type of Japanese production mode originated from the electronic assembly industry. In practice, seru production has been proven to be efficient, flexible, response quickly, and can cope with the fluctuating production demands in a current volatile market. This paper focuses on scheduling problems in seru production system. Motivated by the realty of labor-intensive assembly industry, we consider learning effect of workers and job splitting with the objective of minimizing the total completion time. A nonlinear integer programming model for the seru scheduling problem is provided, and it is proved to be polynomial solvable. Therefore, a branch and bound algorithm is designed for small sized seru scheduling problems, while a local search-based hybrid genetic algorithm employing shortest processing time rule is provided for large sized problems. Finally, computational experiments are conducted, and the results demonstrate the practicability of the proposed seru scheduling model and the efficiency of our solution methods.

Keywords: Seru scheduling; Learning effect; Job splitting; Branch and bound; Genetic algorithm (search for similar items in EconPapers)
Date: 2022
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Citations: View citations in EconPapers (3)

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DOI: 10.1007/s10479-021-04515-0

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