Dynamic Optimal Ground Water Remediation Including Fixed and Operation Costs

Abstract

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.

Integration of Optimal Dynamic Control and Neural Network for Groundwater Quality Management

“…The procedure adapted a groundwater remediation problem from the example in Chang and Hsiao (2002). Figure 2 displays a hypothetical confined aquifer with dimensions of 600 m by 1200 m to demonstrate algorithm performance described above.…”

“…Optimal remediation design is based on groundwater flow and pollutant transport simulation. Typical flow and pollutant transport models of contaminated aquifers predict the effectiveness of a single prospective pumping strategy in P&T remediation (McKinney and Lin 1994;Chang and Hsiao 2002;Hsiao and Chang 2005). Solving field-scale problems related to groundwater remediation design is time-consuming, as hundreds to thousands of numerical simulation runs may be required for searching optimal pumping strategies.…”

“…Several studies have investigated the feasibility of coupling optimization technique with groundwater flow and transporting simulation to design P&T systems (Chang et al 1992;McKinney and Lin 1994;Wang and Zheng 1998;Chang and Hsiao 2002;Chu et al 2005;Chang et al 2007). Significant advances over the past two decades apply optimized ground water management (Gorelick et al 1984;Jones et al 1987;Yeh 1992;Ahlfeld et al 1988;McKinney and Lin 1994;Chang and Hsiao 2002;Hsiao and Chang 2002;Hsiao and Chang 2005;Chu and Chang 2010). However, the solution of the optimal groundwater contamination problem is computationally difficult because the nonconvexities inherent in the contaminant transport equation (Ahlfeld and Sprong 1998).…”

Application of Optimal Control and Fuzzy Theory for Dynamic Groundwater Remediation Design

“…The method is primarily useful for decontaminating groundwater with highly soluble pollutants by pumping out contaminated groundwater and treating the water. The feasibility of coupling optimization techniques with groundwater flow and transporting simulation to design P&T systems has been extensively studied (Chang and Shoemaker 1992;Culver and Shoemaker 1993;McKinney and Lin 1994;Wang and Zheng 1998;Chang and Hsiao 2002;Chu et al 2005;Chang et al 2007). Containing the contamination by removing contaminated ground water should be a dynamic process.…”

Optimal control algorithm and neural network for dynamic groundwater management

“…Using CDDP requires that dynamic optimal groundwater management accommodate these situations. CDDP significantly reduces dimensionality difficulties associated with nonlinear dynamic groundwater management problems (Jones et al, 1987;Chang et al, 1992;Culver and Shoemaker, 1992;Chang and Hsiao, 2002;Chang et al, 2007). Jones et al (1987) used CDDP algorithm for unsteady, nonlinear, groundwater management problems.…”