Energy-saving fuzzy cascade scheduling method and system for regional gathering cooperative production

By establishing a mathematical model and LBCOF algorithm for the cascade scheduling problem of energy-saving type II fuzzy distributed flow workshops and multiple flexible work workshops, the dynamic uncertainty and energy efficiency balance problems in multi-factory collaborative scheduling are solved, and efficient multi-objective optimization and stable production scheduling are achieved.

CN120995901AActive Publication Date: 2025-11-21LANZHOU UNIVERSITY OF TECHNOLOGY
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Patent Information

Application Number
CN202511517523.8
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2025-10-23
Publication Date
2025-11-21
Estimated Expiration
2045-10-23

AI Technical Summary

Technical Problem

Existing technologies struggle to handle dynamic uncertainties, multi-objective collaborative optimization, and the balance between energy efficiency and response speed in multi-factory collaborative scheduling. In particular, in regionally clustered industries, traditional scheduling models and algorithm frameworks exhibit limitations and inefficiencies in complex production scenarios, failing to meet actual production needs.

Method used

A mathematical model for the energy-saving Class II fuzzy distributed flow shop and multi-flexible work shop cascade scheduling problem is adopted, combined with the LBCOF algorithm, including a modeling module, an encoding module, an optimization module and an output module. Through local search, destruction and recombination, genetic operation and learning-assisted strategies, multi-objective optimization and dynamic decision-making are achieved.

Benefits of technology

It provides a systematic theoretical framework, improves the stability and convergence speed of the algorithm, expands the search range of the understanding space, adapts to complex scenarios, achieves the goals of improving resource utilization and green production, and meets the actual production needs in heterogeneous environments with multiple factories.

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Abstract

The invention relates to the technical field of intelligent production and manufacturing, in particular to an energy-saving fuzzy cascade scheduling method and system for regional gathering cooperative production, and aims to solve the composite problems of supply chain cascade scheduling heterogeneous factory resource allocation, multi-stage time accumulation effect, uncertainty interference and the like in regional cooperative transformation in the manufacturing industry. According to the method, a double-layer collaborative optimization framework is assisted through integrated learning, the uncertainty of quintuple interval fuzzy quantization processing, transportation and assembly time is adopted, an initial Q value matrix is generated through a pre-training layer, self-adaptive operator selection is achieved in combination with a dynamic decision-making layer, and local search, damage recombination and genetic operation are executed by multiple sub-groups. According to the method, the energy-saving second-class fuzzy distributed flow shop and multi-flexible job shop cascade scheduling problem model is effectively defined, three-segment coding and full-process energy consumption calculation are supported, and the overall scheduling efficiency and the energy efficiency balance capability of the regional aggregation industry are remarkably improved.
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