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High-efficiency scheduling optimization method

An optimized scheduling and high-efficiency technology, applied in control/regulation systems, comprehensive factory control, instruments, etc., can solve problems such as non-optimal solution results and slow algorithm convergence speed, and achieve the effect of improving population diversity

Inactive Publication Date: 2018-02-16
ZHEJIANG UNIV
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AI Technical Summary

Problems solved by technology

However, many algorithms tend to fall into local optimum during the solution process, and at the same time, there are defects such as slow algorithm convergence speed and non-optimal solution results when solving complex large-scale problems

Method used

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Embodiment Construction

[0056] The present invention will be described in detail below according to the accompanying drawings.

[0057] Assume that there are 9 jobs to be arranged in the 2-stage mixed flow workshop, and each stage has 5 processors. Operation time and processor reference required for each job Figure 9 .

[0058] refer to figure 1 . The method flow includes the following steps:

[0059] 1) The values ​​of matrix size and p are based on Figure 9 enter.

[0060] 2) Parameter setting, the number of individuals in the population N, the maximum number of iterations t max , random parameter α, individual attraction β 0 , medium absorption rate γ; where N=20, t max =500, α=0.5, β 0 =0.2, γ=1.

[0061] 3) Population individual initialization.

[0062] Generate population X=(x 1 ,x 2 ,...,x N ), the sth individual x in the population s =(x s1 ,...,x s9 ), x sj It is a real number between 0 and 9, s∈{1,2,…,N}, j∈{1,2,…,9}. due to individual x s The coordinates of are contin...

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Abstract

The invention discloses a high-efficiency scheduling optimization method. According to the invention, a swarm intelligence optimization method based on a variable neighborhood search algorithm is employed for solving a multi-processing-task mixed flow work shop scheduling problem, and the variable neighborhood search algorithm which comprises five neighborhood structures is introduced to a fireflyalgorithm, thereby improving the diversity of populations, improving the local search capability of the algorithm, and improving the search precision of the algorithm. Moreover, a work adjustment rule is proposed, thereby increasing the convergence rate of the algorithm, and enabling the method to achieve the optimal scheduling at high efficiency. The method can effectively shorten the idle timeof a processing machine, improves the production efficiency, and improves the economic benefits after scheduling.

Description

technical field [0001] The invention relates to the field of production scheduling, in particular to an efficient optimal scheduling method. Background technique [0002] The hybrid flow-shop scheduling problem (HFSP) was first proposed by Salvador in 1973 based on the background of the petroleum industry. HFSP has a strong engineering background, and scheduling problems in mass production, manufacturing, assembly, transportation, and synthesis, as well as Internet services, container handling, etc., can all be attributed to HFSP. With the rapid development of modern production technology and parallel computer systems, many practical multi-stage scheduling problems require that workpieces be processed simultaneously by several processors in each stage. Therefore, the hybrid flow-shop scheduling problem with multiprocessor tasks (HFSPMT) is more widely used in the actual production process. [0003] The solution algorithms of HFSPMT can be divided into three categories: exa...

Claims

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Application Information

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IPC IPC(8): G05B19/418
CPCG05B19/41865G05B2219/32252Y02P90/02
Inventor 刘兴高应炅王雅琳阳春华桂卫华
Owner ZHEJIANG UNIV
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