Negotiation-Based Capacity Planning with a Learning Mechanism Using Adaptive Neuro-Fuzzy Inference System
碩士 === 國立臺灣科技大學 === 工業管理系 === 104 === In decentralized manufacturing environment with multiple factories that are scattered geographically, the complexity of production systems increases, and capacity planning and allocation of resources have become a significant concern that affects system performa...
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| Format: | Others |
| Language: | en_US |
| Published: |
2016
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| Online Access: | http://ndltd.ncl.edu.tw/handle/r237wt |
| Summary: | 碩士 === 國立臺灣科技大學 === 工業管理系 === 104 === In decentralized manufacturing environment with multiple factories that are scattered geographically, the complexity of production systems increases, and capacity planning and allocation of resources have become a significant concern that affects system performances. This study focuses on the development of an integrated framework to allocate limited budget in a multiple-factory environment. We develop a negotiation framework with learning mechanism to allocate autonomously finite budget provided by a headquarter and to facilitate the use of limited manufacturing resources that are scattered over individual factories. The outcome of the experiments shows good prediction of the opponent offers during negotiation, so it enables the reduction of negotiation time.
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