Scheduling parallel machines with sequence dependent set-up times in job shop industries using GA and SA

ABSTRACT

In this paper, an unprecedented and practicable job shop scheduling problem (JSSP) is presented as the fuzzy hybrid reentrant job shop and parallel machines scheduling with sequence dependent set-up times. The JSSP is identified as a complicated optimisation situated in NP-hard (Non-deterministic polynomial) problems in turn. In addition, we have incorporated some applicative constraints such as: reentrant work flows, parallel machines and uncertainty as fuzzy processing times and fuzzy sequence dependent set-up times simultaneously. In a real-world job shop problem, determining exact values for the problem's factors is usually difficult, especially in human–dependent ones. Inserting uncertainty to the problem makes the job shop scheduling more practical and realistic. There is considerable work in the fuzzy job shop scheduling problem (FJSSP) but none of them has applied such complexity. A real-life work field has been studied for evaluating solving methodologies. Two distinguished metaheuristics – simulated annealing (SA) and genetic algorithm (GA) – are investigated and compared to achieve minimum of maximum fuzzy completion times (or fuzzy makespan C _max). The comparison results show the same performance of both proposed SA and GA in small-scale models. But in large-scale problems GA overcomes SA significantly.

KEYWORDS:

• Hybrid reentrant job shop
• parallel machines
• fuzzy processing times
• fuzzy sequence dependent set-up times
• SA
• GA

Disclosure statement

No potential conflict of interest was reported by the author.

Additional information

Notes on contributors

Ghorbanali Mohammadi

Ghorbanali Mohammadi is associate professor in the Industrial engineering department at Qom university of Technology. He received his Ph.D. degree in Industrial Engineering from Brunel university, London United Kingdom. Moreover, he received B.Sc. and M.Sc. 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 45 papers in reputable Journals; he also published four books named Heuristic algorithms, Operational Research and Human factors Engineering.