P. Yunusoglu, S. Topaloglu Yildiz
Constraint programming (CP) is an effective tool for solving constrained optimization problems. However, it is still being stuck at a solution due to the computational complexity of the highly constrained scheduling problems. Therefore, in this paper, we propose a CP-based solution approach to solve the lot streaming problem encountered in flexible job shops. In the proposed solution approach, the CP model is used as a local search to solve the neighborhoods. Moreover, to enhance the performance of the CP model, we develop efficient branching strategies based on different variable and value ordering heuristics. We extend the flexible job shop scheduling problem benchmark instances regarding the lot streaming problem. The computational study is carried out with different scenarios in real-world settings. The proposed CP-based solution approach tackles the computational complexity of the problem. The computational results show that the CP-based solution approach outperforms the novel CP model in medium- and large-size instances.
Keywords: Lot Streaming, Flexible Job Shop Scheduling, Constraint Programming, Branching Strategies
Scheduled
TB1 Scheduling 1
June 10, 2021 11:15 AM
1 - GB Dantzig
