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Mixed the process job scheduling problem research

Author: ZhaoChunMin
Tutor: YangQiFan
School: Zhejiang University
Course: Operational Research and Cybernetics
Keywords: Shop scheduling Genetic Algorithms Simulated annealing algorithm Mixed strategy
CLC: TP11
Type: Master's thesis
Year: 2008
Downloads: 84
Quote: 2
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Abstract


Job Shop Scheduling is one of the most difficult problems in the manufacturing system is a hot research topic , but also theoretical research has become important research issues in the field of the CIMS (Computer Integrated Manufacturing Systems, Computer Integrated Manufacturing System) . Effective scheduling optimization plays an important role in the research and application of technology for manufacturing enterprises to improve production efficiency , reduce production costs , and thus more and more attention of scholars . Workshop limited resources restrict the ability to effectively use the workshop of existing resources to complete the task , the fastest speed of response to market demand to promote manufacturing enterprises can 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 . However, due to resource constraints and process constraints coexist , so far computational complexity theory show that the majority of the scheduling problem is NP-hard (Non-deterministicPolynomial-Hard, non - deterministic polynomial ) problem , generally speaking , there is no polynomial time algorithm . In addition, a variety of dynamic events in the actual workshop is difficult to predict , so shop scheduling problem is extraordinarily complex , and so far has not a universal effective scheduling policy . This paper first introduces the methods and the development status of shop scheduling research at home and abroad , expounded the basic concepts, principles and methods of genetic algorithms and simulated annealing algorithm . Followed by a detailed mathematical analysis study of mixing processes job scheduling , and simplified mathematical description . Finally, a hybrid strategy to combine the two .

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