The multi-factory supply chain problem is investigated to determine the production and transportation scheduling of jobs which are allowed to be transported by batches. This is a mixed-integer optimization problem, which could be challenging to solve. The problem incorporates two parts: (1) assigning jobs to appropriate batch, and (2) scheduling jobs of batches for production and transportation. Based on the problem structure and because of its NP-hardness characteristics, Benders decomposition is recognized as a suitable approach. This approach decomposes the problem into assignment master problem and scheduling sub-problem. This would facilitate the solution procedure. By comparing performance of the proposed algorithm with an exact approach: Branch and Bound, It is achieved that it is able to find the near optimal solution in smaller computational times than the Branch and Bound.
Karimi, N., & Davoudpour, H. (2017). A Benders decomposition algorithm for multi-factory scheduling problem with batch delivery. Scientia Iranica, 24(2), 823-833. https://doi.org/10.24200/sci.2017.4064
MLA
Karimi, N., & Davoudpour, H. "A Benders decomposition algorithm for multi-factory scheduling problem with batch delivery", Scientia Iranica, 24, 2, 2017, 823-833. doi: 10.24200/sci.2017.4064
HARVARD
Karimi N., Davoudpour H. (2017). 'A Benders decomposition algorithm for multi-factory scheduling problem with batch delivery', Scientia Iranica, 24(2), pp. 823-833. doi: 10.24200/sci.2017.4064
CHICAGO
N. Karimi & H. Davoudpour, "A Benders decomposition algorithm for multi-factory scheduling problem with batch delivery," Scientia Iranica, 24 2 (2017): 823-833, doi: 10.24200/sci.2017.4064
VANCOUVER
Karimi N., Davoudpour H. A Benders decomposition algorithm for multi-factory scheduling problem with batch delivery. Scientia Iranica. 2017;24(2):823-833. doi: 10.24200/sci.2017.4064
