The results of the proposed algorithm are very competitive.
📌 3 Key Takeaways
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Objective & Hypothesis:Traditional permutation flowshop scheduling problem (PFSP), which has unlimited buffer space, has been interested over the fifty years by several authors to account for many industrial applications.
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Key Findings & Data:However, some industries, such as the aerospace industry and other sectors processing industrial waste, have different blocking conditions due to the limited or lack of buffer area between their machines.
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Conclusion & Impact:The results of the proposed algorithm are very competitive.
🔬Design:Modeling & Simulation
📍Scope:Comprehensive Sample
⚙️Variables:Flowshop Scheduling · Adaptive Large Neighborhood Search · Constraint Programming
Abstract
Traditional permutation flowshop scheduling problem (PFSP), which has unlimited buffer space, has been interested over the fifty years by several authors to account for many industrial applications. However, some industries, such as the aerospace industry and other sectors processing industrial waste, have different blocking conditions due to the limited or lack of buffer area between their machines. In this study, a mixture of different blocking types is considered to solve PFSP with the total flow time criterion regarding several blocking types. A constraint programming model is proposed to solve the PFSP with mixed blocking constraints (MBFSP). Due to the problem's NP-hard nature of the problem, an adaptive large neighborhood search heuristic is proposed to solve the large size instances. The results of the proposed algorithm are very competitive.
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