A novel hybrid SA/GA algorithm for solving an integrated cell formation–job scheduling problem with sequence-dependent set-up times. Issue 3 (2nd July 2016)

• Record Type: Journal Article
• Authors: Rafiei, Hamed; Rabbani, Masoud; Gholizadeh, Hassan; Dashti, Hossein
• Is Part Of: International journal of management science and engineering management. Volume 11:Issue 3(2016)
• Page Start: 134
• Page End: 142
• Publication Date: 2016-07-02
• Subjects: cell formation -- cellular manufacturing -- genetic algorithm -- group scheduling -- simulated annealing; C02 -- C61 -- C63 -- C69 -- D24; Management science -- Periodicals; Engineering -- Management -- Periodicals; Engineering -- Management; Management science; Periodicals; 658.005
• DOI: 10.1080/17509653.2014.1003109
• Languages: English
• ISSNs: 1750-9661

Abstract

Abstract : Cell formation problems attempt to assign machines and products to manufacturing cells so as to minimize inter-cell moves, in which some other aspects of the manufacturing system, such as time of order delivery, have been mostly neglected. To fill the gap, this paper addresses the cell formation problem and job scheduling simultaneously. To this end, a mixed integer nonlinear program is proposed to address issues related to both cell formation and job scheduling in a job shop layout. The proposed model minimizes the costs of operations and transportation in a single-period setting, since the problem considered is a strategic problem. Moreover, a hybrid simulated-annealing/genetic (SA/GA) algorithm is developed to cope with the complexity of the proposed model. Finally, numerical experiments are reported that validate the performance of the hybrid algorithm developed.