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Open Access Issue
End-to-End Scheduling of Single-Arm Cluster Tools with Multiple Wafer Types
Complex System Modeling and Simulation 2026, 6(2): 164-178
Published: 02 June 2025
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Downloads:19

The rapid advancement in circuit manufacturing technology has enabled the reduction in circuit width. Consequently, a single wafer can now accommodate more chips, allowing for smaller lot sizes to meet diverse customer needs. Manufacturers aim to use a single production line to simultaneously produce multiple types of wafers for various customizations. However, this presents two challenges: (1) Different types of wafers require different processing routes, necessitating a highly adaptable scheduling algorithm for producing various wafer types in the same production line; (2) producing multiple wafer types involves several state transitions, whereas existing research primarily focuses on single-state transitions. To address these challenges, we propose an end-to-end scheduling method for single-arm cluster tools handling multiple wafer types (ESM-SMWT). First, ESM-SMWT employs a genetic algorithm to optimize the sequence in which wafers enter the cluster tool, improving the utilization of shared and parallel processing modules. Next, integer programming is used to achieve end-to-end scheduling, from the processing of the first wafer at the start of a lot to the completion of the last wafer. Additionally, the new robotic arm strategy we propose significantly reduces the number of robotic arm activities. Through theoretical proofs and extensive experiments, the practical effectiveness of ESM-SMWT is validated.

Open Access Issue
Automatic Optimization of Guidance Guardrail Layout Based on Multi-Objective Evolutionary Algorithm
Complex System Modeling and Simulation 2024, 4(4): 353-367
Published: 30 December 2024
Abstract PDF (3.6 MB) Collect
Downloads:65

Guardrails commonly play a significant role in guiding pedestrians and managing crowd flow to prevent congestion in public places. However, existing methods of the guardrail layout mainly rely on manual design or mathematical models, which are not flexible or effective enough for crowd control in large public places. To address this limitation, this paper introduces a novel automated optimization framework for guidance guardrails based on a multi-objective evolutionary algorithm. The paper incorporates guidance signs into the guardrails and designs a coding-decoding scheme based on Gray code to enhance the flexibility of the guardrail layout. In addition to optimizing pedestrian passage efficiency and safety, the paper also considers the situation of pedestrian counterflow, making the guardrail layout more practical. Experimental results have demonstrated the effectiveness of the proposed method in alleviating safety hazards caused by potential congestion, as well as its significant improvements in passage efficiency and prevention of pedestrian counterflow.

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