Improved particle swarm optimization algorithm for solving job-shop scheduling problem
A particle swarm algorithm and job shop technology, applied in the field of solving job shop scheduling problems with algorithms, can solve the problems of unprocessed particle information abnormalities, disturbances, narrowing the search range, etc., to reduce blind search time, reduce interference, and avoid unnecessary The effect of deterministic reasoning
Inactive Publication Date: 2017-05-03
SICHUAN YONGLIAN INFORMATION TECH CO LTD
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[0007] The purpose of the present invention is to overcome the existing in the prior art: the particle swarm algorithm is easy to fall into a local optimum; the particle swarm algorithm only processes the current particle The current optimal solution is perturbed to narrow the search range
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[0039] Because the traditional particle swarm optimization algorithm has fast search speed, high efficiency and simple algorithm, it is suitable for real-time processing. However, it does not handle discrete optimization problems well, and it is easy to fall into local optimum. Therefore, in order to solve these problems, this algorithm first improves the method of randomly generating the initial solution of the traditional PSO: introduces the weighted average method to set the initial solution of the particles; secondly, improves the mean shift algorithm: uses the improved mean shift The algorithm predicts the next state of the initial solution, compares the predicted solution with the current optimal solution, and takes the better solution as the current optimal solution, which solves the abnormal change of particle information that is not considered in the particle swarm optimization algorithm ; Again, the introduction of the tabu search algorithm to further update the part...
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The invention provides an improved particle optimization algorithm for solving a job-shop scheduling problem, and relates to the technical field of job-shop scheduling. Improvements are performed in order to solve a problem that the traditional particle swarm optimization algorithm is poor in processing for a discrete optimization problem and easily falls into local optimum. Firstly, an improvement is performed on a traditional PSO (Particle Swarm Optimization) method which generates an initial solution randomly, and a weighted average method is introduced to set the initial solution of particles; secondly, an improvement is performed on a mean shift algorithm, the next state of the initial solution is predicted by using the improved mean shift algorithm, a predicted solution is compared with the current optimal solution, the better solution is enabled to act as the current optimal solution, and a problem that abnormal changes in particle information are not considered in the particle swarm optimization algorithm is solved; and thirdly, a tabu search algorithm is introduced to perform further update on the particle information, and the problem that the particle swarm optimization algorithm easily falls into local optimum is just solved.
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[0001] Field [0002] The invention relates to the field of job shop scheduling, in particular to using an algorithm to solve job shop scheduling problems. Background technique [0003] Job-Shop Scheduling Problem (JSP) is one of the core and focus of manufacturing execution system research, its research not only has great practical significance, but also has far-reaching theoretical significance. JSP is to rationally allocate resources according to product manufacturing needs, and then achieve the purpose of rationally utilizing product manufacturing resources and improving enterprise economic benefits. JSP is a co-existing problem in the product manufacturing industry. It is closely related to the factory management and product manufacturing levels of Computer Integrated Manufacturing Systems (CIMS), and is an important research topic in the field of CIMS. JSP is a typical NP-hard problem, and its research will definitely have a meaningful impact on the research of NP probl...
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IPC IPC(8): G05B19/418
CPCG05B19/41865G05B2219/32252
Inventor 姜艾佳胡成华
Owner SICHUAN YONGLIAN INFORMATION TECH CO LTD