Integrated scheduling of production and rail transportation

• Published in: Computers & industrial engineering Vol. 74; pp. 240 - 256
• Main Authors: Hajiaghaei-Keshteli, M., Aminnayeri, M., Fatemi Ghomi, S.M.T.
• Format: Journal Article
• Language: English
• Published: New York Elsevier Ltd 01.08.2014; Pergamon Press Inc
• Subjects: Algorithms; Delivery scheduling; Integrated production–distribution; Mathematical models; Rail transportation; Railroad transportation; Scheduling; Single machine scheduling; Studies; Supply Chain Optimization; Supply chains; Synchronism; Taguchi experimental design; Taguchi methods; Trains; Transportation; Integrated production–distribution; Rail transportation; Supply Chain Optimization; Single machine scheduling; Taguchi experimental design
• ISSN: 0360-8352; 1879-0550
• DOI: 10.1016/j.cie.2014.05.026

•An integrated production and transportation model, which considers rail transportation, is firstly developed.•Different destinations of the trains, trains’ capacities, and different transportation costs are the main aspects of the model.•The problem and its constraints are discussed and detailed.•A heuristic, two metaheuristics and some related procedures are developed.•Taguchi experimental design method is utilized to improve their performance. Nowadays, the most used, efficient and inexpensive mode of transportation between supply chain partners is the rail transportation. To the best of our knowledge, there is no research reported to date, which addresses the problem of synchronization of production and rail transportation. In this work, an integrated production and transportation model, which considers rail transportation, is firstly developed to deliver the orders from a facility to the customers (warehouses). The problem is to determine both production schedule and rail transportation allocation of orders to optimize customer service at minimum total cost. Different destinations of the trains, trains’ capacities, and different transportation costs are the main aspects of the work which are considered. In order to tackle such an NP-hard problem, a heuristic, two metaheuristics and some related procedures are developed. Besides, Taguchi experimental design method is utilized to set and estimate the proper values of the algorithms’ parameters to improve their performance. For the purpose of performance evaluation of the proposed algorithms, various problem sizes are employed and the computational results of the algorithms are compared with each other. Finally, we investigate the impacts of the rise in the problem size on the performance of our algorithms.