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Schedule optimization method based on flexible scheduling

An optimization method and flexible technology, applied in the direction of program control, electrical program control, control/regulation system, etc., can solve the problems of complex, difficult to consider the factors of agitation production, and many factors affecting production, so as to reduce the The effect of production energy consumption, production idle time reduction and production cost reduction

Active Publication Date: 2019-12-20
天津开发区精诺瀚海数据科技有限公司
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AI Technical Summary

Problems solved by technology

However, due to the many and complex factors affecting production in the actual workshop production process, it is difficult to consider most of the factors that disturb production in the sequence sequence generated by a single algorithm, and it still lacks reliable guiding significance for the actual production execution

Method used

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  • Schedule optimization method based on flexible scheduling
  • Schedule optimization method based on flexible scheduling
  • Schedule optimization method based on flexible scheduling

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Embodiment Construction

[0061] The present invention will be further described in detail below in conjunction with the accompanying drawings and specific embodiments.

[0062] In the design process of the scheduling optimization method based on flexible scheduling in the present invention, the optimization algorithm uses a full amount of data. In the particle swarm optimization algorithm, the present invention regards the full amount of data as all data points in a closed two-dimensional space, wherein each data point contains multiple sub-points, first find a certain data point as the optimal data point, and Take a certain subpoint of the data point as the global optimal point and take it out, then merge this data point with the next optimal data point, find the next optimal point in the merged subpoint, and pass it on in turn to form one such as figure 1 The data processing structure of the swirl is shown. In other parts of the model, the structural form of sequentially processing data points in ...

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Abstract

The invention discloses a schedule optimization method based on flexible scheduling. The schedule optimization method comprises the steps of: taking CR values of a customer order as a convergence formula of a particle swarm for searching an optimal solution on the basis of a time decomposition method; embedding an optimized particle swarm into an artificial immune algorithm based on a working process decomposition method and a mathematical model structural decomposition method to obtain an initial production schedule sequence; establishing a multi-objective optimization model; calculating a production bottleneck procedure and a highest-efficiency working procedure; matching product models with the complementary bottleneck working procedure and the highest-efficiency working procedure, andmutating original solutions in combination with artificial immunity to generate a plurality of schedule sequences; and calculating the affinity of the plurality of schedule sequences so as to screen the solutions and finally generate an optimal schedule sequence. The schedule optimization method based on flexible scheduling is combined with the actual workpiece production process, the scheduling plan is reasonably generated, and the effects of shortening the idle production time, reducing the production energy consumption and reducing the production cost are achieved.

Description

technical field [0001] The invention relates to the technical field of production scheduling, in particular to a scheduling optimization method based on flexible scheduling. Background technique [0002] Under the background of German Industry 4.0, the competition in the global market is becoming increasingly fierce. As one of the favorable conditions for occupying the market, reasonable production planning and scheduling are increasingly valued by enterprises and academia. Among them, data-driven production scheduling is particularly important. Because production scheduling under big data can give enterprises more detailed data information, and can take into account factors such as production capacity, personnel skills, material availability, tooling and mold constraints, and then formulate pre-planning schedules through intelligent optimization algorithms. [0003] Production scheduling is the process of assigning production tasks to production resources. The most basic ...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G05B19/418
CPCG05B19/41865G05B2219/32252Y02P90/02
Inventor 金玉蓉孙敬哲王汉奇赵宇高立超孙跃华
Owner 天津开发区精诺瀚海数据科技有限公司
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