Using two metaheuristic algorithms for scheduling parallel machines with sequence dependent set-up times in job shop industries

Abstract

Nowadays, scheduling problem in the field of production planning has been considered by many researchers and this issue is used in various industries. Using the same parallel machines reduces the queue of WIP behind the machine and also increases production. Since scheduling problems in large scale are NP-hard, to solve them, metaheuristic algorithms are used. In this paper, Ant colony optimisation and Harmony Search algorithm are used to solve the problem as well as comparison with two other algorithms and finally, their performance is analysed and the efficient algorithm is investigated.

KEYWORDS:

• Scheduling
• job shop
• Ant colony
• harmony search

Disclosure statement

No potential conflict of interest was reported by the author(s).

Notes

1 Harmony memory consideration rate.

2 Pitch adjustment rate.

3 Design of the experiment.

Additional information

Notes on contributors

Ghorbanali Mohammadi

Ghorbanali Mohammadi is an associate professor in the Industrial engineering department at Qom University of Technology. He received his PhD degree in Industrial Engineering from Brunel University, London, UK. Moreover, he received BSc and MSc degrees both in Industrial Engineering from Oklahoma and Tennessee state universities, respectively. His research interest areas include sequencing and scheduling, GA, SA, ACO, Tabu search and human factors engineering. He has published more than 50 papers in reputable Journals; he also published four books named Heuristic algorithms, Operational Research and Human factors Engineering.

Erfan Moaddabi

Erfan Moaddabi received a BS degree in Industrial Engineering from the Damghan University, Damghan, Iran (2019). He is currently working towards the MS degree at the Department of Industrial Engineering, Qom University of Technology, Iran. His research interests include production scheduling and metaheuristic algorithms.