國內過去對於裝潢修繕工程產生之廢棄物，因缺乏產生源數量與流向申報之管理法令規定，導致其廢棄物產生數量與流向並未全面掌握，隨意棄置情事多有所聞，依據裝潢及修繕工程處理業者粗估每年約產生700萬立方公尺之裝潢修繕廢棄物。行政院環境保護署於九十四年度推動「營建資源再利用推動計畫」，未來將於各縣轄市境內設置廢棄物回收站與再利用廠，加強管理因裝潢修繕所產出之廢棄物，期望自廢棄物產出源頭管理開始至綠營建工程應用分階段進行妥善規劃，俾使有用之營建資源能納入資源回收體系，而後進一步回收再製成為再生建材，落實及提昇資源回收再利用成效，達到營建副產物全回收零廢棄之目標。 本研究結合區位理論的概念，建構出一設置區位最佳化評選基本模式，並運用基因演算法（Genetic Algorithms）來求解設施配置問題，藉著結合各項限制式目標以及有效縮短搜尋可行解的時間，進一步求解出廢棄物回收站與再利用廠設置之最佳化區位選擇，可提供給決策者作為選定最適宜區位之參考依據。 本研究以桃園縣設置區位來進行實證研究對象，依據九十二年度縣境人口數與戶數推估各區位廢棄物產生量，並透過運距最短及設置總成本最小化之目標，求解出廢棄物回收站與再利用廠設置之最佳化區位，此種求解模式和步驟考量各區位廢棄物產生數量與運輸距離等影響因素，其所求解出來的結果亦證明本研究模式理論的可行性。 Under the global development of sustainable construction, the reuse and recycling of demolition wastes of household renovation is getting more and more attentions, following the reuse and recycling of building and construction demolition wastes. The government in Taiwan is contemplating a plan aiming to increase its reuse and recycling rates. The idea is for a local government to solicit private investment for establishing a BOT-based recycling plant. Meanwhile collective stations are set up by the local government to collect the household renovation wastes free and to transport them to the recycling plant. At the end, the recycling products produced by the recycling plants will be used in the local public construction projects. Thus a chain of recycling the demolition wastes of household renovation can be formed. This research focuses on the problem of where to put the collective stations and the recycling plant in order to minimize the transportation distance, considering the amounts of demolition wastes of household renovation generated in each location and the traveling distances between locations. A GA model is developed to determine the number of collecting stations required and their locations, as well as the location of the recycling plant. Only one recycling plant is considered in the system at current stage. A semi-pseudo case of Taoyuan County is used for model demonstration and validation. The preliminary result shows the soundness of the developed optimization model.
