Exact and heuristic algorithms for the just-in-time scheduling problem in a batch processing system

• Published in: Computers & operations research Vol. 80; pp. 173 - 183
• Main Authors: Parsa, N. Rafiee, Karimi, B., Husseini, S.M. Moattar
• Format: Journal Article
• Language: English
• Published: New York Elsevier Ltd 01-04-2017; Pergamon Press Inc
• Subjects: Algorithms; Batch processing; Batch processing machine; Branch & bound algorithms; Branch and bound; Dynamic programming; Heuristic; Integer programming; Just in time; Just-in-time scheduling; Linear programming; Scheduling; Studies; Just-in-time scheduling; Batch processing machine; Dynamic programming; Branch and bound; Heuristic
• ISSN: 0305-0548; 1873-765X; 0305-0548
• DOI: 10.1016/j.cor.2016.12.001

•A just-in-time scheduling problem on a batch processing machine is considered.•A mixed integer linear programming model is developed.•A DP algorithm to find the optimal schedule for a given set of batches is presented.•Several heuristics, a lower bounding method, and a B&B algorithm are proposed.
Batch processing systems are commonly used in many different environments such as chemical and semiconductor industries. In this research, a just-in-time scheduling problem in a batch processing system is investigated. Minimization of total earliness and tardiness of the jobs with respect to a common due date is considered as the objective function. First, the research problem is formulated as a mixed integer linear programming model. Then, to find the optimal schedule for a predetermined set of batches, a dynamic programming algorithm is proposed. Based on the proposed dynamic programming algorithm, several heuristics are also developed. A lower bounding method is presented, and then a branch and bound algorithm is proposed to solve the problem optimally. To demonstrate the performance of the proposed algorithms, several computational experiments are conducted.