| Summary: | 碩士 === 國立臺灣科技大學 === 建築系 === 93 === In recent years, Taiwan government has been troubled with the decision on the resource allocation of the historic building restoration. For example, Tainan City Government, owns over 100 historic buildings with high tourist economic value, more than any other cities in Taiwan, experiences headache every year when the actual cost of restoration always exceeds the city council approved budget.
Obviously, the government lacks an open, fair, justified, and transparent assessment platform to assist in the decision making on the resource allocation. For this cause, this study comes out a “Supporting System Model” as a platform for the government to make an intelligent decision.
The “Supporting System Model” is also a process of professional data gathering, information evaluation, knowledge analyses, intelligent decision-making on the resource allocation of Taiwan historic building restoration.
The model consists of four job setting/selecting/groupings as “Setting Job Priority of Value and Importance”, “Job Selecting by Priority and Possible Synergy”, “Job Grouping by Geography”, and “Job Grouping by Nature”. Then, the optimization method of “Genetic Algorithms” is applied to calculate for an intelligent and professional alternative. Therefore, this “Supporting System Model” on the resource allocation of the historic building restoration can be abbreviated as “RAHBR-SS Model”.
|
|---|
