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The Study of Job-shop Scheduling Problem of Maintenance Machine Manufacture Based-on GA

Author: WuMingHua
Tutor: YangRenFeng
School: Chang'an University
Course: Mechanical Design and Theory
Keywords: Maintenance machinery Production scheduling Genetic Algorithms MATLAB
CLC: TP18
Type: Master's thesis
Year: 2007
Downloads: 86
Quote: 1
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Abstract


Computer Integrated Manufacturing System (CIMS) can significantly improve the overall economic efficiency of enterprises , which is the current domestic and foreign major medium-sized hotspot of research and implementation . Production planning and scheduling system as an important part in the implementation of CIMS Engineering , computer integrated manufacturing system functional structure model indispensable level . The scheduling problem is a combinatorial optimization problem is NP problem , in recent years, a variety of intelligent computing methods have been gradually introduced into the scheduling problem , such as genetic algorithms , simulated annealing algorithm . Maintenance machinery production varieties , small batch ( or even a single-piece production ) , workshop limited resources restrict the effective use the workshop of available resources to complete the task , the fastest speed of response to market demand , prompting the manufacturing The ability of the business to win the competition in the market . Task scheduling production objectives and constraints for each object to be processed to determine the specific processing route , the time machine and operation . The excellent scheduling strategy for optimal production system , improve economic efficiency has a great role . This paper studied the conservation of mechanical job shop scheduling problem . The paper systematically introduces job-shop scheduling theory and its development , optimization algorithm for the job shop scheduling theory and its characteristics ; maintenance machinery for the production process , describes the overview of the workshop , the existing production process and conventional scheduling methods ; maintenance machinery and production shop scheduling model ; chromosome encoding method and the genetic operators , using genetic algorithm to solve the scheduling problem . Matlab powerful numerical calculation ability and many library functions to write the algorithm , the test solution performance of the algorithm by simulation examples . Demonstrated the program algorithm results in better equipment resources to organize production , to take full advantage of the strong guiding significance for the actual production of the workshop .

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CLC: > Industrial Technology > Automation technology,computer technology > Automated basic theory > Artificial intelligence theory
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