Operational strategies for seru production system: a bi-objective optimisation model and solution methods

Yılmaz Ö. F.

INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH, vol.58, no.11, pp.3195-3219, 2020 (SCI-Expanded) identifier identifier

  • Publication Type: Article / Article
  • Volume: 58 Issue: 11
  • Publication Date: 2020
  • Doi Number: 10.1080/00207543.2019.1669841
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus, ABI/INFORM, Aerospace Database, Business Source Elite, Business Source Premier, Communication Abstracts, Compendex, INSPEC, Metadex, zbMATH, Civil Engineering Abstracts
  • Page Numbers: pp.3195-3219
  • Keywords: seru production system, NSGA-II, AUGMECON2, worker transfer, bi-objective workforce scheduling problem, LINE-CELL CONVERSION, EPSILON-CONSTRAINT METHOD, CONVEYOR ASSEMBLY-LINE, NSGA-II ALGORITHM, LOCAL SEARCH, COST, SERIAL
  • Karadeniz Technical University Affiliated: Yes


In recent years, the interest in seru production system (SPS) has increased to enhance the flexibility of production systems. Because the worker resource in an SPS is critical for adapting to changes in demand, this study focuses on workforce-related operational strategies rarely considered for SPS. To this end, for the first time in the literature, a bi-objective workforce scheduling problem is addressed by considering the interseru worker transfer in SPS. A novel optimisation model is proposed to achieve two objectives, that of minimising makespan and reducing workload imbalance among workers. Because it is proved that the problem falls within a non-deterministic polynomial-time hardness (NP-hard) class, non-dominated sorting genetic algorithm-II (NSGA-II) is employed to solve large-sized problems. For small-sized problems, the second version of the augmented epsilon-constrained (AUGMECON2) method is implemented and Pareto-optimal solutions are obtained. A set of evaluation metrics is considered to compare two different operational strategies in terms of the desired objectives. The computational results indicate that allowing worker transfer leads to better results for all metrics. The main contribution of the present study is to provide a novel optimisation model for the addressed problem to compare two operational strategies by considering the heterogeneity inherent of workers.