A matheuristic approach for an integrated lot-sizing and scheduling problem with a period-based learning effect
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arXiv
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| Main Authors: | , , , |
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| Format: | Preprint |
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2024
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| _version_ | 1866917887529189376 |
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| author | Rohaninejad, Mohammad Vahedi-Nouri, Behdin Tavakkoli-Moghaddam, Reza Hanzálek, Zdeněk |
| author_facet | Rohaninejad, Mohammad Vahedi-Nouri, Behdin Tavakkoli-Moghaddam, Reza Hanzálek, Zdeněk |
| contents | This research investigates a multi-product capacitated lot-sizing and scheduling problem incorporating a novel learning effect, namely the period-based learning effect. This is inspired by a real case in a core analysis laboratory under a job shop setting. Accordingly, a Mixed-Integer Linear Programming (MILP) model is extended based on the big-bucket formulation, optimizing the total tardiness and overtime costs. Given the complexity of the problem, a cutting plane method is employed to simplify the model. Afterward, three matheuristic methods based on the rolling horizon approach are devised, incorporating two lower bounds and a local search heuristic. Furthermore, a post-processing approach is implemented to incorporate lot-streaming possibility. Computational experiments demonstrate: 1) the simplified model performs effectively in terms of both solution quality and computational time; and 2) although the model encounters challenges with large-scale instances, the proposed matheuristic methods achieve satisfactory outcomes; and 3) it can be inferred that the complexity of the models and solution methods are independent of the learning effect; however, the value of learning effect may impact the performance of the lower bounds; 4) in manufacturing settings, where the lot-streaming is possible, incorporating post-processing can drastically improve the objective function; 5) the impact of the period-based learning effect in the results is significant, and the model's sensitivity to time-based parameters (e.g., learning rate) is more than cost-based ones (e.g., tardiness cost). |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2412_16222 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | A matheuristic approach for an integrated lot-sizing and scheduling problem with a period-based learning effect Rohaninejad, Mohammad Vahedi-Nouri, Behdin Tavakkoli-Moghaddam, Reza Hanzálek, Zdeněk Optimization and Control This research investigates a multi-product capacitated lot-sizing and scheduling problem incorporating a novel learning effect, namely the period-based learning effect. This is inspired by a real case in a core analysis laboratory under a job shop setting. Accordingly, a Mixed-Integer Linear Programming (MILP) model is extended based on the big-bucket formulation, optimizing the total tardiness and overtime costs. Given the complexity of the problem, a cutting plane method is employed to simplify the model. Afterward, three matheuristic methods based on the rolling horizon approach are devised, incorporating two lower bounds and a local search heuristic. Furthermore, a post-processing approach is implemented to incorporate lot-streaming possibility. Computational experiments demonstrate: 1) the simplified model performs effectively in terms of both solution quality and computational time; and 2) although the model encounters challenges with large-scale instances, the proposed matheuristic methods achieve satisfactory outcomes; and 3) it can be inferred that the complexity of the models and solution methods are independent of the learning effect; however, the value of learning effect may impact the performance of the lower bounds; 4) in manufacturing settings, where the lot-streaming is possible, incorporating post-processing can drastically improve the objective function; 5) the impact of the period-based learning effect in the results is significant, and the model's sensitivity to time-based parameters (e.g., learning rate) is more than cost-based ones (e.g., tardiness cost). |
| title | A matheuristic approach for an integrated lot-sizing and scheduling problem with a period-based learning effect |
| topic | Optimization and Control |
| url | https://arxiv.org/abs/2412.16222 |