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Flexible workshop scheduling method

A technology of workshop scheduling and scheduling methods, applied in control/regulation systems, computing models, artificial life, etc., to improve the quality of solutions, solve premature convergence, and expand the search range

Pending Publication Date: 2021-01-05
NANJING UNIV OF AERONAUTICS & ASTRONAUTICS +1
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  • Abstract
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  • Claims
  • Application Information

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Problems solved by technology

In addition, based on the simulated annealing algorithm to expand the search range of the field, solve the problem of premature convergence, and improve the solution quality of the algorithm

Method used

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Embodiment 1

[0022] This embodiment provides that, firstly, a mathematical model oriented to the flexible job shop scheduling problem is established. The traditional production mode of job shop and flow shop has been difficult to adapt to the needs of modern enterprises for personalized and green manufacturing. Therefore, a production mode for mixed-line flexible job shop will be studied, and a mathematical scheduling model will be established for the mixed-line production mode.

[0023] Such as figure 1 As shown, the implementation steps of the hybrid particle swarm optimization algorithm include: initializing all parameters, initializing the population particles, calculating the fitness value of each particle, initializing the individual best particle and the global best particle, and the domain search strategy, and finally outputting the global optimal particle .

[0024] Such as figure 2 As shown, process-based and machine-based coding methods are used to complete the initializatio...

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Abstract

The invention discloses a flexible workshop scheduling method, which comprises the following steps of: 1, firstly, establishing a mathematical model for a flexible job-shop scheduling problem, and initializing all parameters; 2, completing particle initialization by adopting a coding mode based on a process and a machine; 3, taking crossover operation in a genetic algorithm as an updating strategyof particles; taking crossover operation in a genetic algorithm as a particle updating strategy of a process part; taking the mutation operation as a particle updating strategy of the machine part; taking a mutation operation as a particle updating strategy of a global optimal particle; and step 4, taking the mutation operation in the genetic algorithm as a domain search strategy of a machine part, simulating the kick of the annealing algorithm in the search process, and finally outputting globally optimal particles to realize scheduling optimization of production elements of the job shop.

Description

technical field [0001] The invention belongs to the field of production system optimization, in particular to a scheduling method with multi-objective optimization capability, specifically a flexible job shop scheduling method based on a hybrid particle swarm algorithm. Background technique [0002] With the continuous upgrading of the production mode of the manufacturing industry, it presents the characteristics of multi-variety, small batch, and mixed flow. There are more and more types of orders, production links, equipment types, and technical states in the production environment, which leads to complex production control. Traditional job shop scheduling methods and manual management have been difficult to achieve efficient, accurate and optimized production management. Intelligent scheduling technology for mixed-line flexible manufacturing workshops. Using the hybrid particle swarm optimization algorithm to solve the flexible job shop scheduling problem not only effect...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06Q10/04G06Q10/06G06Q50/04G06N3/00G05B19/418
CPCG06Q10/04G06Q10/06316G06Q50/04G06N3/006G05B19/41865G05B2219/32252Y02P90/30
Inventor 朱海华张毅唐敦兵聂庆玮张泽群王立平宋家烨
Owner NANJING UNIV OF AERONAUTICS & ASTRONAUTICS