Aquifer Remediation Design: Nonlinear Programming and Genetic Algorithms

by Daene C. McKinney, (A.M.ASCE), Univ of Texas, Austin, United States,
Gregory B. Gages, Univ of Texas, Austin, United States,
Min-Der Lin, Univ of Texas, Austin, United States,

Document Type: Proceeding Paper

Part of: Water Policy and Management: Solving the Problems


Nonlinear programming and genetic algorithm solutions of a pump-and-treat aquifer remediation design model are presented and discussed. These models find the minimum cost design of the combined pumping and treatment components of the remediation system and include the fixed costs of system construction and installation as well as operation and maintenance. The fixed cost terms of the objective function have been incorporated successfully into a conventional nonlinear programming formulation using a penalty coefficient method. Groundwater management problems are highly nonlinear and nonconvex mathematical programming problems. As such there is no guarantee that a global or even robust optimum will be found by nonlinear programming algorithms. Furthermore, some system component cost functions are either discontinuous or highly complicated and it is very difficult to calculate or estimate the derivatives of the cost functions with respect to the design parameters. Genetic algorithms provide an alternative method of solution for these problems and are capable of identifying globally optimal solutions.

Subject Headings: Computer programming | Algorithms | Mitigation and remediation | Groundwater management | Benefit cost ratios | Pumps | Nonlinear analysis

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