Please use this identifier to cite or link to this item: `http://hdl.handle.net/11455/5558`
 標題: 模擬退火演算法在地下水復育優選問題之應用The Application of Simulated Annealing GroundWater Remedation Problem 作者: 葉恩仲Yeh, En-chung 關鍵字: simulated annealing模擬退火groundwater remedationoptimization地下水復育最佳化 出版社: 環境工程學系 摘要: 由於地下水復育優選問題中包含許多非凸之非線性方程式及不等式，傳統梯度式（gradient-type）搜尋方法在求解的過程中，常因其特性而造成搜尋陷入局部解中難以跳脫，以致無法獲得全域最佳解。模擬退火法屬於啟發式演算法的一種，近年來發展出所謂的啟發式優選技術如遺傳演算法、禁忌搜尋法、模擬退火法等，強調具有跳脫局部解及接受劣化解之特性，本研究利用模擬退火法求解地下水復育優選問題；並將模擬退火法與遺傳演算法結合發展GA-SA混合模式，期使發展出更具強健性的地下水管理工具。 研究中以地下水復育優選問題為例，並分別將模擬退火法及GA-SA混合模式針對均質(homogeneous)及非均質(heterogeneous)之地下含水層污染復育優選問題進行測試，以了解各個最佳化方法在不同非線性程度最佳化問題之表現。研究結果發現，GA-SA混合模式在求解各個案例時，其最佳解及平均表現均較模擬退火法為優，然而在求解效率方面則與模擬退火法差異不大。The optimization problems of groundwater remediation system have the feature that the objective function and constraints may be noncovex as well as nonlinear. Classical gradient-based algorithms including nonlinear programming and descent methods have not been successful in solving such kind of problems. In general, these methods converge to a local optimum easily. Simulated annealing (SA)is one of the heuristic algorithms which have becmoe the most widely used tool for solving many optimization problems. These methods, such as genetic algorithms (GA), simulated annealing and tabu search, are well-known by their capability of global search. In this paper, SA is introduced and applied to the optimization of groundwater management problems cast in combinational form and a new hybrid model GA-SA which combines GA and SA is also developed. In the hybrid model, GA is served as a coarse-grained optimizer, then SA served as a fine-grained optimizer. The results show that the performance of hybrid model is more efficient and robust than SA. URI: http://hdl.handle.net/11455/5558 Appears in Collections: 環境工程學系所

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