A computational optimization method for scheduling resource-constraint sequence-dependent changeovers on multi-machine production lines. (15th April 2021)

• Record Type: Journal Article
• Authors: Saeed Osman, Mojahid
• Is Part Of: Expert systems with applications. Volume 168(2021)
• Publication Date: 2021-04-15
• Subjects: Scheduling -- Changeover -- Sequence-dependency -- Integer programming; Expert systems (Computer science) -- Periodicals; Systèmes experts (Informatique) -- Périodiques; Electronic journals; 006.33
• DOI: 10.1016/j.eswa.2020.114265
• Languages: English
• ISSNs: 0957-4174

Abstract

Abstract: This paper presents an algorithmic method that hybridizes solution procedures with an optimization model for solving the problem of scheduling and allocating changeover tasks. This problem involves a limited number of changeover workers with different skills and a set of sequence-dependent changeover tasks on a multi-machines production line, where executing each task requires a particular type and number of workers. For solving this allocation and scheduling problem, the paper identifies and investigates three priority rules expressed as objective functions to minimize the total changeover time and maximize the workers' utilization while satisfying changeover task-sequence-dependency and worker-limit constraints. For illustrating the applicability and suitability of the proposed approach, a real-world case problem of a 10-machine production line is considered for scheduling and allocating 34 sequence-dependent changeover tasks to 4 workers. The computational effort and time for optimizing each of the three identified objective functions using the proposed method were significantly undersized. The key results are the effective changeover time and workers' utilization provided by the proposed hybrid approach.