A method and system for dynamic scheduling of flexible job shops considering machine aging

By introducing a multi-objective mathematical model and adaptive response strategy for machine aging effect into the dynamic scheduling of flexible workshops, the scheduling deviation problem caused by machine aging is solved, achieving efficient and intelligent scheduling optimization and improving the adaptability and practicality of the algorithm.

CN121303637BActive Publication Date: 2026-05-26JIUJIANG UNIV +1
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
JIUJIANG UNIV
Filing Date
2025-09-10
Publication Date
2026-05-26

AI Technical Summary

Technical Problem

Existing technologies fail to effectively consider performance degradation caused by machine aging when dealing with dynamic scheduling in flexible workshops, resulting in deviations between scheduling schemes and actual production status. Furthermore, the response mechanism is not adaptive enough, making it difficult to achieve efficient and accurate resource allocation and scheduling optimization in dynamic environments.

Method used

A dynamic multi-objective mathematical model is established that deeply couples machine aging effect with uncertain processing time. Quantitative indicators are obtained through environmental change detection, and static optimization or dynamic response strategies are adaptively selected. By combining hybrid initialization and hierarchical response strategies, efficient and intelligent scheduling of dynamic environments can be achieved.

Benefits of technology

It achieves rapid and efficient response to dynamic environments, improves the quality of multi-objective optimization solution sets, enhances the consistency between scheduling models and physical reality, improves the practicality and adaptability of algorithms, and enables refined management in complex and uncertain environments.

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Abstract

This invention belongs to the field of intelligent manufacturing and production scheduling technology, and discloses a dynamic scheduling method and system for flexible workshops that considers machine aging. The invention designs a hierarchical environmental response strategy, which first assesses the severity of environmental changes. When the changes are not drastic, only a lightweight local optimization strategy is used for fine-tuning; when the changes are more drastic, a global reconstruction strategy combining knowledge transfer, re-initialization, and targeted repair is activated. This allows the algorithm to intelligently allocate computing resources according to the severity of environmental changes, avoiding blind global searches and greatly improving the algorithm's response speed and operating efficiency. This design effectively balances the algorithm's exploration and utilization capabilities, ensuring rapid convergence while maintaining population diversity, thereby obtaining a set of Pareto optimal solutions with good convergence and wider distribution.
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