Details

Autor(en) / Beteiligte

• Ahmadi, Ehsan
• Zandieh, Mostafa
• Farrokh, Mojtaba
• Emami, Seyed Mohammad

Titel

A multi objective optimization approach for flexible job shop scheduling problem under random machine breakdown by evolutionary algorithms

Ist Teil von

• Computers & operations research, 2016-09, Vol.73, p.56-66

Ort / Verlag

New York: Elsevier Ltd

Erscheinungsjahr

2016

Quelle

Alma/SFX Local Collection

Beschreibungen/Notizen

• This paper addresses the stable scheduling of multi-objective problem in flexible job shop scheduling with random machine breakdown. Recently, numerous studies are conducted about robust scheduling; however, implementing a scheme which prevents a tremendous change between scheduling and after machine breakdown (preschedule and realized schedule, respectively) can be critical for utilizing available resources. The stability of the schedule can be detected by a slight deviation of start and completion time of each job between preschedule and realized schedule under the uncertain conditions. In this paper, two evolutionary algorithms, NSGA-II and NRGA, are applied to combine the improvement of makespan and stability simultaneously. A simulation approach is used to evaluate the state and condition of the machine breakdowns. After the introduction of the evaluation criteria, the proposed algorithms are tested on a variety of benchmark problems. Finally, through performing statistical tests, the algorithm with higher performance in each criterion is identified. •A methodology for addressing multi objective flexible job shop scheduling problem is proposed.•Stability and makespan considered to optimize simultaneously in presence of machine breakdown.•NRGA, NSGAII, and simulation used to tackle the problem.•In three criteria NSGAII is leading algorithm and for two criteria NRGA is the leading one.