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A method for solving flexible job shop scheduling based on an improved whale algorithm

A technology for flexible operation and workshop scheduling, which is applied in the direction of calculation, calculation model, nonlinear system model, etc.

Pending Publication Date: 2019-06-14
CHANGAN UNIV
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Problems solved by technology

[0003] Although scholars have proposed various meta-heuristic algorithms for solving FJSP in recent years, including improved bacterial foraging algorithm based on cloud computing, hybrid genetic algorithm and particle swarm algorithm, etc., there is still no such algorithm that can solve FJSP. All the optimal solutions of FJSP, so scholars are still actively exploring in order to find a solution method that can better solve the optimal solution

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  • A method for solving flexible job shop scheduling based on an improved whale algorithm
  • A method for solving flexible job shop scheduling based on an improved whale algorithm
  • A method for solving flexible job shop scheduling based on an improved whale algorithm

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Embodiment 3

[0176] Using the improved whale algorithm, a 3×6 FJSP scheduling problem is used as an example to simulate and solve it. The processing information table is shown in Table 4. Its corresponding iterative convergence curve is as follows Figure 5 As shown, the obtained scheduling result Gantt chart is as follows Image 6 shown.

[0177] Table 4 Processing information table

[0178]

[0179]

[0180] The present invention proposes a kind of improved whale optimization algorithm for solving FJSP to the characteristics of the flexible job shop scheduling problem: 1) algorithm adopts two-stage coding mode, designs a kind of population based on chaos reverse learning strategy and search method The initialization method is used to improve the quality of the initial population; secondly, the variable neighborhood search operation is performed on the current optimal individual to enhance the local search ability of the algorithm; in addition, the nonlinear convergence factor and...

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Abstract

The invention discloses a method for solving flexible job shop scheduling based on an improved whale algorithm. The method comprises the following steps: 1) establishing a mathematical model of a flexible job shop scheduling problem; 2) setting algorithm parameters and generating an initial population; 3) obtaining a current optimal scheduling solution; 4) judging whether the current number of iterations is greater than the maximum number of iterations; if yes, outputting a scheduling solution; if not, judging whether the counter value of the current optimal individual is not smaller than a preset value or not; if yes, carrying out variable neighborhood search operation, and updating a scheduling solution; if not, converting the scheduling solution into a whale individual position vector,and retaining the whale individual corresponding to the scheduling solution; and 5) updating whale individual position information by adopting an improved whale algorithm, converting the whale individual position vector into a scheduling solution to complete population updating, adding 1 to the number of iterations, and returning to the step 3). According to the method disclosed by the invention,all optimal solutions of flexible job shop scheduling can be well solved, and the solving speed and precision are improved.

Description

technical field [0001] The invention belongs to the field of flexible job shop scheduling, and relates to a method for solving flexible job shop scheduling based on an improved whale algorithm. Background technique [0002] The flexible job-shop scheduling problem (Flexible Job-shop Scheduling Problem, FJSP) is an extension of the classic scheduling problem, because it considers the characteristics of the flexible processing path of the workpiece, it is more in line with the actual situation of the workshop production, but the reduction of machine constraints also increases Therefore, the solution algorithm of this problem has become one of the research hotspots in the field of workshop scheduling in recent years. At present, the intelligent optimization algorithm is the main method to solve this problem. It provides more ideas and approaches for solving FJSP, and has attracted extensive attention of scholars at home and abroad. [0003] Although scholars have proposed vari...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06Q10/06G06N7/08G06N3/00
Inventor 栾飞李富康蔡宗琰吴书强杨嘉
Owner CHANGAN UNIV
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