| Against the background of economic globalization,market demand changed frequently. In order to not to be eleminated in the intense competition, manufacturing enterprises needed to response the market more quickly.So,many manufacturing enterprises,especially the small and medium ones, whose capacity was worse,have been abandoning traditional manufacturing mode and began to seek more cooperation between enterprises. By carrying out networked manufacturing,the manufacturing enterprises could response the market faster,better and cheaper.Network-based bidding was the best way to carry out resource configuration. The result of bidding influenced the reslut of the resource configuration. This paper reserached the key techniques in the process of Network-based bidding,includeing the technology of formulating bidding strategy which would be used by the resource owner and the approach to selection an optimistic resource which would be used by the resource asker were payed more attention. The main content of this researcg were as follows:(1)In order to help the resource owner to make a better bidding strategy,a approach which combined by rough set and BP neural network was used to analyze the historical bidding data and mining the knowledge about bidding problem. When reducing the feature of the bidding problem,an algorithm for attribute reduction based on dependence degree was advanced.(2)In order to help the resource asker to select the best manufacturing,the extension evaluation approach was used. The material element model of resource evaluation problem was built and different dependent function was used according to the type of the index. So the veracity of the result was ensured.(3)According to the research,a Network-based bidding system which was the subsystem of the manufacturing resource configuration system based on ASP platform had been developed. The research results presented in this paper has been thoroughly proved Via the system's application. |
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