研究目的
Investigating the use of a deterministic tabu search algorithm for solving large-scale dynamic complex job shop scheduling problems in semiconductor fabricating facilities, focusing on sequencing, routing, and batching to minimize job tardiness.
研究成果
The study concludes that a deterministic tabu search algorithm with a novel combination of neighborhoods for sequencing, routing, and batching can effectively solve large-scale complex job shop scheduling problems in semiconductor manufacturing. The proposed method achieves lower total tardiness values in a timely fashion compared to common dispatch rules.
研究不足
The study focuses on semiconductor manufacturing, and the applicability of the proposed method to other industries is not explored. The computational experiments are based on specific benchmark instances, which may not cover all possible scenarios in real-world applications.
1：Experimental Design and Method Selection:
The study employs a deterministic tabu search algorithm for sequencing, routing, and batching operations in semiconductor manufacturing. It involves constructing an initial schedule using priority rules and iteratively improving it through sequencing, routing, and batching stages.
2：Sample Selection and Data Sources:
Benchmark data sets SET1 and SET2 from semiconductor manufacturing are used, representing typical size and structure of the industry.
3：List of Experimental Equipment and Materials:
Not explicitly mentioned.
4：Experimental Procedures and Operational Workflow:
The algorithm starts with an initial schedule, then iteratively applies sequencing, routing, and batching neighborhoods to improve the schedule. Performance is evaluated based on total tardiness and computational time.
5：Data Analysis Methods:
The study compares the performance of different neighborhoods and methods based on their ability to reduce total tardiness and computational effort.
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