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Collaborative design task decomposition and task scheduling method

Author: ChenDaChuan
Tutor: ZhangRongGuo
School: Taiyuan University of Science and Technology
Course: Computer Software and Theory
Keywords: Collaborative design Task decomposition Coupled task set Fuzzy design structure matrix Task scheduling
CLC: TP391.72
Type: Master's thesis
Year: 2011
Downloads: 97
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Abstract


Computer supported collaborative design (CSCD) is a network-based experts in different fields to participate in off-site and distributed development technology . By multidisciplinary many experts to work together to complete a common product design tasks , thereby improving the efficiency , in order to achieve the purpose of shortening the product design cycle , enhance the market competitiveness of products . Task decomposition and task scheduling problem is an important prerequisite for collaborative design , can effectively solve this problem , a direct impact on the smooth progress of the collaborative design process . Therefore, to carry out research on collaborative design task decomposition and task scheduling method has great significance . This paper first introduces the basic concepts of the collaborative design task decomposition and task scheduling , reviewed its development and research status , to solve the problem by using some of the techniques and methods and summarized , given the task of planning model . For the complex relationship between the product design task decomposition subtasks using fuzzy design structure matrix to build a sub- task model and task decomposition algorithm based on the DSM split algorithm . Through the analysis of the degree of coupling between the coupling task concentrated subtasks , proposed a new strategy of decoupling . Finally, using relevant examples to verify the effectiveness of the use of algorithms and strategies . One for solving this kind of problem of particle swarm algorithm for task scheduling co-design in the discrete NP problem : First, pre - constraint method to generate the initial population , and then design a dual particle encoding , then down harmony search strategy is introduced to solve the particle swarm algorithm is easy to fall into the local optimum defect , and finally through the classic example of the proposed algorithm, simulation , and analysis were compared with the results of other methods , demonstrate that the proposed algorithm optimization ability and faster convergence .

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CLC: > Industrial Technology > Automation technology,computer technology > Computing technology,computer technology > Computer applications > Information processing (information processing) > Machine-assisted technology > Machine -aided design (CAD), aided drawing
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