啟發式演算法在地下水復育優選問題之應用

李姵穎

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啟發式演算法在地下水復育優選問題之應用

The Application of Heuristic Algorithms on the Optimization of Groundwater Remediation Problems

李姵穎 , Masters　　Advisor：林明德　　

繁體中文

非線性規劃；禁忌搜尋法；模擬退火法；遺傳演算法；混合優選模式；地下水復育優選問題； nonlinear programming ； tabu search ； simulated annealing ； genetic algorithms ； hybrid method ； optimization ； groundwater remediation

Abstract │ Reference (39) │ Times Cited (3) │ Altmetrics

Abstract 〈TOP〉

Parallel Abstract 〈TOP〉

The Optimization of groundwater remediation problems often needs to handle multivariate decision and the function of greatly non-linearity, causing difficulties in solution. The conventional method to solve these kinds of problems is nonlinear programming (NLP); however, the search of such traditional method tends to fall into local optimum instead of global optima.
Therefore, heuristic and advanced techniques such as tabu search (TS), simulated annealing (SA), genetic algorithms (GA), and ant algorithms have been developed in recent years to enhance the global optimization ability. This study employs TS, SA, GA, and the conventional NLP to find out the solution of optimization of groundwater remediation problems. Furthermore, due to the searching ability of every algorithm is often circumscribed by its own attribute and each have its own merits and defects, we use GA as pre-processor, combining NLP, TS, and SA respectively as hybrid models (GA-NLP, GA-TS, and GA-SA) to solve optimization of groundwater remediation problems.
Two hypothetical, confined aquifers with homogeneous and heterogeneous hydraulic conductivities are used as case studies. The results show that NLP and GA-NLP converged more quickly to the solutions than other methods; GA-TS obtained the best quality solutions of the minimum pumping rate problems, while GA displayed the most stable and reliable performance. In addition, the results also reveal that hybrid model is able to improve the solution quality and reliability of the groundwater optimization problems.

Reference ( 39 ) 〈TOP〉

Ahlfeld , D. P., Mulvey, J. M., Pinder, G. F., and Wood, E. F. (1988). "Contaminated Groundwater Remediation Design Using Simulation, Optimization, and Sensitivity Theory 1. Model Development." Water Resources Research, 24(3), 431-441.
連結：
Bhallamudi, S. M., Rao, S. V. N., Thandaveswara, B. S., and Srinivasulu, V. (2003). "Optimal groundwater management in deltaic regions using simulated annealing and neural networks." Water Resources Management, 17(6), 409-428.
連結：
Chan Hilton, A. B., and Culver, T. B. (2000). "Constraint handling for genetic algorithms in optimal remediation design." Journal of Water Resources Planning and Management, 126(3), 128-137.
連結：
Chan Hilton, A. B., and Culver, T. B. (2005). "Groundwater remediation design under uncertainty using genetic algorithms." Journal of Water Resources Planning and Management, 131(1), 25-34.
連結：
Chelouah, R., and Siarry, P. (2000). "Tabu search applied to global optimization." European Journal of Operational Research, 123(2), 256-270.
連結：

Times Cited (3) 〈TOP〉

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