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Method for solving dynamic workshop scheduling based on improved genetic algorithm of polychromatic set

A technology of improved genetic algorithm and multi-color set, which is applied in the field of dynamic workshop scheduling based on improved genetic algorithm based on multi-color set, and can solve problems such as premature

Inactive Publication Date: 2018-05-18
SHAANXI UNIV OF SCI & TECH
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Problems solved by technology

However, when the population size is too large, the genetic algorithm has a "premature" convergence problem, that is, the algorithm no longer evolves because it converges to a local optimal solution or the population cannot generate individuals whose performance exceeds that of the parent generation.

Method used

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  • Method for solving dynamic workshop scheduling based on improved genetic algorithm of polychromatic set
  • Method for solving dynamic workshop scheduling based on improved genetic algorithm of polychromatic set
  • Method for solving dynamic workshop scheduling based on improved genetic algorithm of polychromatic set

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Embodiment

[0217] Taking the processing tasks in Table 1 as the basic task information, the optimization goal only considers the shortest total processing time for task completion. The order is set to have 3 pieces of workpieces A, B, and C each, and the genetic parameters are set as follows: the population size is 50, the crossover rate is 0.6, the mutation rate is 0.08, the maximum number of evolutionary bands is 140, and the optimal solution is 121 minutes (the shortest processing time time). Depend on Figure 11 It can be seen from the genetic evolution curve that the improved genetic algorithm can quickly converge from 145 to 121 in the 41st generation. Centralized processing and balanced occupancy of machine tool resources. Figure 12 Gantt chart for scheduling results.

[0218] Note: The process codes of the same color in the figure belong to the same type of workpiece, and the above numbers indicate the code bit sequence number and process number of this type of workpiece in the...

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Abstract

The invention discloses a method for solving dynamic workshop scheduling based on an improved genetic algorithm of a polychromatic set. By adopting the method, a method for solving the dynamic workshop operation scheduling by combining a genetic algorithm and a polychromatic set theory is realized. The improved algorithm combining the genetic algorithm and the polychromatic set theory is applied to the dynamic flexible workshop operation scheduling in order to provide an appropriate algorithm for the dynamic flexible operation workshop scheduling problem, so that the operation time is shortest, the dynamic re-scheduling problem in two cases such as the damage of machine tool equipment and insertion of an emergency key can be solved, the machining time and the machining cost can be reduced,and the dynamic change of a workshop scheduling environment can be handled; and according to the improved genetic algorithm, the dynamic re-scheduling can be carried out in the case of changing a contour matrix and not changing a scheduler program, the solving speed is high, the solving precision is high.

Description

technical field [0001] The invention belongs to the technical field of flexible workshop scheduling and relates to a method for solving dynamic workshop scheduling based on an improved genetic algorithm of a multi-color set. Background technique [0002] The essence of the traditional job shop scheduling problem is to arrange the relationship between tasks and resources reasonably and scientifically, and to predetermine the processing sequence, processing machine tool and processing time of each process. The flexible job shop scheduling problem can be expressed as: when multiple workpieces are processed on multiple machine tools, the process route cannot be completely determined before reprocessing, that is, there may be several processing routes for each workpiece, and the selection status of each route It needs to be determined according to the idle condition of the machine tool. Because FJSP increases the uncertainty of the machine tool, expands the solution domain, and ...

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Application Information

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IPC IPC(8): G06Q10/06G06Q50/04
CPCG06Q10/0631G06Q50/04Y02P90/30
Inventor 栾飞石冰洁陈梦瑶李媛鸣来春为傅卫平刘二宝王川
Owner SHAANXI UNIV OF SCI & TECH
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