Dynamic optimal ground water remediation including fixed and operation costs.
In time-varying ground water remediation, the lack of an optimal control algorithm to simultaneously consider fixed costs and time-varying operating costs makes it nearly impossible to obtain an optimal solution. This study presents a novel algorithm that integrates a genetic algorithm (GA) and constrained differential dynamic programming (CDDP) to solve this time-varying ground water remediation problem. A GA can easily incorporate the fixed costs associated with the installation of wells. However, using a GA to solve for time-varying policies would dramatically increase the computational resources required. Therefore, the CDDP is used to handle the subproblems associated with time-varying operating costs. A hypothetical case study that incorporates fixed and time-varying operating costs is presented to demonstrate the effectiveness of the proposed algorithm. Simulation results indicate that the fixed costs can significantly influence the number and locations of wells, and a notable total cost savings can be realized by applying the novel algorithm herein.
Chang
Liang-Cheng
LC
Department of Civil Engineering, National Chiao Tung University, Hsinchu, Taiwan, Republic of China. lcchang@chang.cv.nctu.edu.tw
Hsiao
Chin-Tsai
CT
D000465:Algorithms; D003198:Computer Simulation; D005618:Fresh Water / Q000737:chemistry*; D008962:Models, Theoretical; D018508:Water Purification / Q000191:economics / Q000379:methods*