Multi-shift planning scheduling method based on improved variable neighborhood genetic algorithm

A genetic algorithm and multi-shift technology, applied in the field of intelligent manufacturing, can solve the problems of low scheduling flexibility, gaps in scheduling results, and low labor efficiency, so as to expand the search range, ensure full utilization, and improve convergence speed The effect on the quality of the settlement

Active Publication Date: 2019-04-16
JIANGSU UNIV OF SCI & TECH
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Problems solved by technology

[0004] Aiming at the problems of low labor efficiency, low scheduling flexibility and gap between scheduling results and actual needs in the planning and scheduling of discrete manufacturing enterprises, a multi-shift planning based on improved variable neighborhood genetic algorithm was invented. Scheduling method, which solves the scheduling problem taking into account the actual production status of the workshop, user needs and each equipment shift

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  • Multi-shift planning scheduling method based on improved variable neighborhood genetic algorithm
  • Multi-shift planning scheduling method based on improved variable neighborhood genetic algorithm
  • Multi-shift planning scheduling method based on improved variable neighborhood genetic algorithm

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[0029] The preferred technical solutions of the present invention will be described in detail below in conjunction with the accompanying drawings.

[0030] In this scheduling method, the variable neighborhood genetic algorithm is used, and the selection operation of the genetic algorithm adopts the combination of roulette selection and random competitive selection method, which avoids the shortcomings of too much randomness in roulette selection, and the crossover operation adopts random number Random gene segment crossover, expanding the search range, combining the mutation operation with the variable neighborhood algorithm, taking the chromosome with the best fitness in the neighborhood of the mutated chromosome as the final mutated chromosome, after the selection, crossover and mutation operations are completed, use the last The individual with the best iterative fitness replaces the individual with the worst iterative fitness, avoiding the prematurity of the variable neighb...

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Abstract

The invention discloses a multi-shift planning scheduling method based on an improved variable neighborhood genetic algorithm, and the method comprises the steps: assessing the priority according to whether the sum of the importance degree of customers, the order value, the processing time length and the remaining processable time is an emergency single comprehensive index, and taking a productiontask with the higher priority as a priority scheduling of a production task to be scheduled. Compared with the prior art, the method has the advantages that the priority production of emergency orderand short delivery date production tasks is guaranteed, the convergence speed and the quality of solution are improved, the full utilization of bottleneck equipment resources is guaranteed, and bottleneck front equipment can be orderly produced according to the processing sequence of bottleneck procedures.

Description

technical field [0001] The invention relates to a planning and scheduling method based on an improved variable neighborhood genetic algorithm, which belongs to the field of intelligent manufacturing. Background technique [0002] Planning and scheduling is the process of arranging the processing time and processing equipment of each process of the production order according to the delivery date of the production order of the enterprise, the production capacity of each equipment, and the comprehensive index of inventory. Order delivery time indicators and a plan that can balance equipment processing and rationally utilize various resources. In discrete manufacturing enterprises characterized by multiple varieties and small batches, there are many production orders, and in the case of complex workshop conditions, the workload of manual planning and scheduling is huge, and the scheduling cost is also greatly increased. In recent years, the planning and scheduling method based ...

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Application Information

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IPC IPC(8): G06Q10/04G06Q10/06G06Q50/04G06N3/12
CPCG06N3/126G06Q10/04G06Q10/0631G06Q50/04Y02P90/30
Inventor 方喜峰陆蓓蕾吴家家张胜文张辉
Owner JIANGSU UNIV OF SCI & TECH
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