Optimal remediation design in groundwater systems by intelligent techniques

Hone Jay Chu*, Chin Tsai Hsiao, Liang-Jeng Chang

*Corresponding author for this work

Research output: Contribution to journalConference articlepeer-review

6 Scopus citations


This research develops an optimal planning model for pump-treatinject based groundwater remediation systems. Optimizing the design of the pump-treat-inject system is a nonlinear, dynamic and discrete optimization problem. This study integrates the Genetic Algorithm (GA) and Differential Dynamic Programming (DDP) to solve this highly complex problem. The proposed model considers both the cost of installing wells (fixed cost) and the operating cost of pumping, injection and water treatment. Minimizing the total cost and meeting the water quality constraints, the model computes the optimal number and location of wells, as well as the associated optimal pumping and injection schemes. This work also investigates many factors that affect the optimal design of a remediation system, such as, various numerical cases revealing the time-varying pumping and injection rate, and the requirement to balance the total volume between pumping and injection that can significantly influence the optimal design.


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