Workshop layout optimization method based on sparrow search algorithm: a new approach

ABSTRACT

Reasonable workshop layout can reduce the transportation distance, reduce the production cost and improve the production efficiency. Aiming at the problem of unreasonable workshop layout, this paper takes an actual case as the research object and studies its workshop layout. Firstly, the mathematical model with the objectives of minimizing logistics transportation cost and maximizing non-logistics relationship is established. Then, the sparrow search algorithm (SSA) is used to find the optimal layout that satisfies the objective function. Finally, Flexsim software is used to simulate the layout scheme. The results show that compared with the genetic algorithm and the original layout scheme, the layout scheme obtained by the SSA algorithm reduces the total transportation distance by 26 m and 325 m, and improves the non-logistic relationship by 1.6% and 24.84%, respectively. Optimizing the layout using SSA algorithms increases product productivity, which is a good improvement over the original workshop layout.

Graphical abstract

KEYWORDS:

• Workshop layout
• optimization
• mathematical model
• sparrow search algorithm

Disclosure statement

Authors confirm that there is no funding or financial support received from any organization or institution for the research work presented in this paper.

Author contributions

Shenghao Bi: Conceptualization, Methodology, Software, Visualization, and Writing-original draft. Liangshan Shao: Supervision, and Writing-review & edit. Jiatian Zheng: Software, and Visualization. Rui Yang: Visualization.

Data availability statement

The data used to support the findings of this study are available from the corresponding author upon request.

Additional information

Notes on contributors

Shenghao Bi

Shenghao Bi is a master’s student at Liaoning Technical University. His major is Industrial Engineering and Management. His research interests include operations optimization, industrial data analytics, sustainable development, and environmental management.

Liangshan Shao

Liangshan Shao is a professor and doctoral supervisor at Liaoning Technical University. He is the subject leader of the first-level doctoral degree in management science and engineering at Liaoning Technical University. His research interests include management systems engineering, management information systems, and big data applications.

Jiatian Zheng

Jiatian Zheng is a master’s student at Liaoning Technical University. Her major is Industrial Engineering and Management. Her research interests include production operations, production safety, and production human factors engineering.

Rui Yang

Rui Yang is a master’s student at Liaoning Technical University. His major is Industrial Engineering and Management. His research interests include production simulation, and production operations optimization.