Ecological Agriculture: Ecological Monitoring and Rehabilitation of Agriculture Landscapes【Department of Civil Engineering / Yang, Ming-Der / Distinguished Professor】
生態農業：農業地景生態監測及復育【土木工程學系/楊明德特聘教授】
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論文篇名 英文：A stochastic multi-objective optimization decision model for energy facility allocation: a case of liquefied petroleum gas station    
中文：能源設施分配的隨機多目標優化決策模型：以液化石油氣站為例
期刊名稱 CLEAN TECHNOLOGIES AND ENVIRONMENTAL POLICY
發表年份,卷數,起迄頁數 2020, 22 (2),389-398
作者 Yang, Ming-Der(楊明德); Chen, Yi-Ping; Wang, Chien-Tsung; Deng, Ming-Jay; Lin, Yu-Hao*; Chen, Ho-Wen
DOI 10.1007/s10098-019-01787-w
中文摘要 為緩解空氣污染問題，政府一直計劃建立更多的液化石油氣站，以激勵駕駛員在台灣使用液化石油氣車輛。這種設施分配問題須考慮加油需求中空間變化，是一多目標優化過程。本研究提出了液化石油氣站分配（SMOMLSA）的隨機多目標優化模型，結合非支配排序遺傳算法II和蒙特卡羅模擬，根據包括投資績效，能源轉換和商機在內的三個權衡目標，對液化石油氣站進行最佳分配。蒙特卡洛模擬程序基於概率分佈在空間網格中生成需要加油的計程車的起始位置，非支配排序遺傳算法II解決多目標之設站問題。 SMOMLSA透過進行實際案例研究得到驗證，結果證明可以提供有關液化石油氣站的最佳分配的資訊，以最小化建設成本，最小化車輛的平均加油距離並最大程度地擴大潛在客戶。
英文摘要 To mitigate air pollution problem, the government has been planning to build more liquefied petroleum gas stations to motivate drivers to use liquefied petroleum gas vehicles in Taiwan. Such facility allocation problem is a multi-objective optimization process considering spatial variation in the need of refueling. This study presents a stochastic multi-objective optimization model for liquefied petroleum gas station allocation (SMOMLSA) that integrates a nondominated sorting genetic algorithm II with a Monte Carlo simulation to optimally allocate liquefied petroleum gas stations according to three trade-off objectives, including investment performance, energy conversion, and business opportunity. Monte Carlo simulation procedure generates the starting location of a taxicab car in need of refueling in the spatial grid based on a probability distribution. Nondominated sorting genetic algorithm II resolves the station location problem with these multi-objectives. The SMOMLSA was validated by conducting a real-world case study. Result depicts that the SMOMLSA can provide information on the optimal allocation of liquefied petroleum gas stations for minimizing construction costs, minimizing average refueling distance for vehicles, and maximizing potential customers.