Evolutionary multi-objective optimization method for dynamic scheduling of scalable pneumatic conveying pipeline
By employing a scalable individual knowledge transfer and reuse method and a group optimization algorithm, the problem of high computational resource consumption in dynamic scheduling of pneumatic conveying systems is solved, achieving rapid response and efficient scheduling, and meeting the multi-objective optimization needs of industrial production.
CN113987959BActive Publication Date: 2026-06-19XIAMEN MINJIANG SMART TECH CO LTD
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- XIAMEN MINJIANG SMART TECH CO LTD
- Filing Date
- 2021-11-16
- Publication Date
- 2026-06-19
Smart Images
Figure CN113987959B_ABST
Abstract
The application provides a pressure dynamic scheduling method for a pneumatic conveying pipeline with scalability, which combines evolutionary multi-objective optimization and machine learning to solve the dynamic scheduling problem of the pneumatic conveying system. The application regards the pressure dynamic adjustment problem of the pneumatic conveying pipeline as a dynamic (static) multi-objective optimization problem, reuses the high-quality solution found in the solving process to generate a better initial population, and thus can significantly improve the performance of the evolutionary algorithm when the demand of the pneumatic conveying system changes, so that the control system has better pressure adjustment capability.
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