In this proposal, we consider a parallel batch processing problem when minimizing the makespan under constraints of arbitrary lot sizes, machine eligibility, time window, and incompatible job families. Different than the previous researches, the machine’s eligibility in our study is not known in advance and will be determined later after the set of materials is assigned to machines. To the best of our knowledge, there is no published papers which deal with the problem. We will formulate a mixed-integer programming model for solving the problem optimally. However, due to the NP-Hardness of our problem, decomposition approach has been successfully applied to solve a variety of batching problems, especially with incompatible job families. Here in this proposal, we will also propose a decomposition-based heuristic algorithm to obtain a near-optimal solution for large-scale instances when the computation time is a concern.
|Effective start/end date||1/08/20 → 31/07/21|
UN Sustainable Development Goals
In 2015, UN member states agreed to 17 global Sustainable Development Goals (SDGs) to end poverty, protect the planet and ensure prosperity for all. This project contributes towards the following SDG(s):
- Parallel batch processing
- Time window constraint
- Machine eligibility determination
- Mixed-integer programming
- Decomposition-based heuristic
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