| Summary: | 碩士 === 國立雲林科技大學 === 環境與安全工程系碩士班 === 91 === The government actively sets the program of regional landfill leachate treatment plants into action at present. In order to match the government’s policy, this research utilizes in a fuzzy multi-objective programming model to investigate the planning of regional landfill leachate treatment plants. In the past, the research mostly focused on the program of wastewater treatment plants, but research about landfill leachate treatment plants was quite rare. Both of traditional programming and optimization model exist some restricts and problems. Such as fuzzy cannot be take into consideration and some uncertain factors exist in decision variables. These result in the contradiction between the solution of optimization mode and real environment problems, which make the program difficult to be realized.
This thesis is based on the expansion of the existed landfill leachate treatment plants and the purchase of equipments. Not only the capital, operating, maintenance and transportation costs are constructed, but also objective function and constraints are established. The shortest single-objective transportation distance, lowest single-objective total cost, integer programming and fuzzy multi-objective programming are included. The planning parameters such as location, number of facility and equipment are determined by above four analyses. In according to these parameters, the idea and methodology are constructed to meet with the policymaker’s cost and be acceptable to the public.
Under the consideration of the shortest transportation distance, the optimal solutions are NT$166,201,000 and NT$87,009,000 per year for reverse osmosis treatment and activated carbon treatment, respectively. Under the consideration of the lowest total cost, the optimal solutions are NT$122,356,000 and NT$72,023,000 per year for reverse osmosis treatment and activated carbon treatment, respectively. Besides, the integer programming analysis shows that two and three new plants should be set up if the transportation distance between two plants were within 30 and 20 km, respectively. The expense is higher in comparison with the expansion of the existed plants.
The fuzzy multi-objective programming combine weighted capital costs, affected population and transportation distance. When all three objectives are considered (the weight and the output variables are 0.2~0.9 and 0.182~0.84, respectively.), the Tounan and Huwei possess high matching degree. The candidate location changes greatly if the weight of policymaker’s favorite objective were selected to be maximum or minimum under different expected values. Bao-Chung is the preferential candidate when both the affected population and transportation distance are considered. When the weight of capital is greater than 0.9, Hsilo is optimal.
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