A Multi-objective scheduling of hybrid manufacturing systems with walking workers

Authors

  • Omer Faruk YILMAZ Istanbul Technical University
  • Mehmet Bulent DURMUSOGLU Istanbul Technical University

DOI:

https://doi.org/10.23055/ijietap.2019.26.5.2810

Keywords:

Hybrid Manufacturing System, Product Sequencing and Scheduling, Multi-objective Evolutionary Algorithm, Worker Intensive Manufacturing System, Walking Workers.

Abstract

Hybrid manufacturing systems (HMSs) are the combination of cells and the functional area. It is more suitable in terms of real-world applications to include workers in the product scheduling problem in these systems by the nature of the cells. The multi-objective product scheduling problem in HMS is addressed together with the worker objectives in this study. Three different objectives are identified for the problem: One of them is the minimization of average flow time, and the other two are the minimization of maximum number of workers and the minimization of maximum number of workers changing. Including the number of workers in the objectives presents a realistic approach as well as bringing problem's novelty out. A new detailed mathematical model which reflects real-world applications is developed for the multi-objective product scheduling problem. NSGA-II which is a metaheuristic algorithm and a local search also developed for the study are combined and utilized together. The algorithm proposed through six different hypothetical cases and the original NSGA-II algorithm are compared, and the efficiency of the proposed algorithm is mentioned in the conclusion.

Author Biographies

Omer Faruk YILMAZ, Istanbul Technical University

Industrial Engineering Department

Mehmet Bulent DURMUSOGLU, Istanbul Technical University

Industrial Engineering Department

Published

2019-10-21

How to Cite

YILMAZ, O. F., & DURMUSOGLU, M. B. (2019). A Multi-objective scheduling of hybrid manufacturing systems with walking workers. International Journal of Industrial Engineering: Theory, Applications and Practice, 26(5). https://doi.org/10.23055/ijietap.2019.26.5.2810

Issue

Section

Production Planning and Control