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Knowledge-driven flexible discrete manufacturing production scheduling optimization method

A knowledge-driven, production-scheduling technology, applied in manufacturing computing systems, control/adjustment systems, program control, etc., can solve problems such as increased complexity of batch machines, increased difficulty in mathematical modeling, and time constraints for special processes, achieving Enhanced local search capabilities, solving batch production and scheduling problems, high efficiency and robustness effects

Active Publication Date: 2021-10-01
WUHAN UNIV OF TECH
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0005] 3. The processing time of special process is limited
[0006] 4. A processing resource can only process a specific process
[0008] 1. Some actual scheduling factors of FCJSP increase the difficulty of mathematical modeling
[0009] 2. Batch machines add another dimension of complexity
[0010] 3. Existing research is difficult to solve the FCJSP problem without modification

Method used

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  • Knowledge-driven flexible discrete manufacturing production scheduling optimization method
  • Knowledge-driven flexible discrete manufacturing production scheduling optimization method
  • Knowledge-driven flexible discrete manufacturing production scheduling optimization method

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Embodiment Construction

[0076] The technical solutions of the present invention will be further specifically described below through the embodiments and in conjunction with the accompanying drawings.

[0077] In order to make the purpose, features and advantages of the present invention more obvious and understandable, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the following The described embodiments are only some, not all, embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without making creative efforts belong to the protection scope of the present invention.

[0078] The hybrid particle swarm optimization algorithm is used to solve the model, the block integration decoding rule is proposed, and the discrete and continuo...

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Abstract

The invention relates to a knowledge-driven flexible discrete manufacturing production scheduling optimization method. A flexible job shop scheduling problem of a batch processor in an evanescent mode casting environment is researched, and a flexible casting job shop scheduling model based on a completion time criterion is established. In combination with the characteristics of casting production, the time execution window is applied to the model. And the model is solved by adopting a hybrid particle swarm optimization (HPSO) algorithm. In the algorithm, a block integration decoding rule is provided to solve the scheduling integration problem. And global search is carried out on the particle swarm optimization algorithm by adopting a discrete type search strategy and a continuous type search strategy. On the basis, a neighborhood tabu search algorithm based on knowledge driving is adopted for local search. A simulation experiment is carried out to verify the feasibility of the optimized model, and the optimized model is applied to lost foam casting. Experimental results show that the algorithm has higher efficiency and robustness than the existing algorithm.

Description

technical field [0001] The invention aims at the flexible job shop scheduling problem of lost foam casting production, and specifically relates to a knowledge-driven flexible discrete manufacturing production scheduling optimization method. Background technique [0002] Lost foam casting (EPC) technology is a new type of casting technology. Due to the characteristics of the casting process itself, there are many limitations in the scheduling problem of lost foam casting workshops, such as flexible job shops with batch machines and time execution windows (time execution window, TEW ), etc., greatly increasing the difficulty and complexity of the scheduling problem, its process route such as figure 1 As shown, the characteristics are as follows: [0003] 1. Determine the processing route for each job under the operating environment of the job shop. [0004] 2. The batch processor can process multiple jobs at the same time, while the single processor can only process one job ...

Claims

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Application Information

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IPC IPC(8): G05B19/418
CPCG05B19/41865G05B2219/32247Y02P90/30
Inventor 王磊闻婧唐红涛张伟艾孜买提·依明江
Owner WUHAN UNIV OF TECH
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