An exact method for job sequencing in a mixed-model assembly line considering feeding lines based on the Benders decomposition approach. Issue 2 (3rd April 2022)

• Record Type: Journal Article
• Authors: Saadi, Anis; Fattahi, Parviz; Rahmanii, Donya; Hosseini, Seyed Mohammad Hassan; Sana, Shib Sankar
• Is Part Of: International journal of management science and engineering management. Volume 17:Issue 2(2022)
• Page Start: 79
• Page End: 92
• Publication Date: 2022-04-03
• Subjects: Mixed-model assembly line -- feeding lines -- Benders decomposition; Management science -- Periodicals; Engineering -- Management -- Periodicals; Engineering -- Management; Management science; Periodicals; 658.005
• DOI: 10.1080/17509653.2021.1937366
• Languages: English
• ISSNs: 1750-9661

Abstract

ABSTRACT: The study proposes an exact method based on the Benders decomposition approach to solve the sequencing problem of the mixed-model assembly line considering feeding lines. A mathematical model is presented and linearized that is capable of solving the small-size scales of the problem. Since the problem is well known as a strongly NP-hard problem, appropriate methods can improve the effectiveness of the outcomes of the model. Therefore, we introduce a Benders decomposition method, which can solve the proposed problem on the medium and large scales. Moreover, a proper accelerator is presented to enhance the performance of the proposed method and to reduce computational time. The outcomes show that the proposed method can provide solutions with a maximum of 4.47% deviation from the optimal for small-scale instances. The result indicates the success of this exact method in solving the problem with different dimensions. In addition, comparing results emphasized that the accelerator used can reduce iterations up to 24% to provide the final solution.