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Application of Improved PSO Algorithms to Job-shop Scheduling System

Author: YinJianLiang
Tutor: HuangMing
School: Dalian Jiaotong University
Course: Applied Computer Technology
Keywords: Particle swarm optimization Niche Uniform Design Shop scheduling
CLC: TP301.6
Type: Master's thesis
Year: 2010
Downloads: 158
Quote: 1
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Abstract


Production scheduling problem is a combinatorial optimization problem . The theoretical study of the optimization method is introduced into the workshop production scheduling field , to improve the performance of the algorithm , to broaden the field of algorithm is applied to improve the algorithm system is a subject of theoretical significance and application value , has important significance . The particle swarm algorithm has been the research focus in the field of agent algorithm . Standard particle swarm algorithm based on an improved particle swarm optimization . New algorithm on two main aspects of the standard particle swarm algorithm make improvements : the introduction of the idea of uniform design to ensure uniform distribution of populations particles , so that a uniform distribution of the particles in the solution space , and then in the evolutionary process of each generation populations run clear algorithm to maintain the diversity of particles , clearing mechanism - based niche evolution effectively explore the various regions of the solution space , to avoid falling into local optimum . These improvements are important to avoid premature algorithm to improve the convergence speed and global search ability . Problems in the application of the standard test set and the actual scheduling of the improved algorithm testing , simulation program show that the algorithm can be completed at a faster speed search and global optimization task in a given range . For manufacturing enterprises , this paper designed a new population initialization method applicable to the actual shop scheduling problem - the uniform initialization particle population , relative to the standard PSO were randomly divided into the shortcomings of the initial population . the division of this paper, the population has a higher diversity . For a factory practical problems , the use of the above techniques , this paper design and a shop scheduling knowledge-based systems platform and improved algorithm embedded system platform , use the improved algorithm to solve practical problems , get the result is a feasible and effective .

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CLC: > Industrial Technology > Automation technology,computer technology > Computing technology,computer technology > General issues > Theories, methods > Algorithm Theory
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