Table 1 Key features and limitations of previous optimization tools
From: Groundwater remediation design using physics-based flow, transport, and optimization technologies
Tool identification | Key features and limitations |
|---|---|
GWM: Ground-Water Management Process for the U.S. Geological Survey (USGS) MODFLOW-2000 (Ahlfeld, et al., 2005) | ● Performs optimization using Linear Programming (LP) or Sequential Linear Programming (SLP). |
● Tightly integrated to the MODFLOW code. | |
● Handles only confined flow and mildly non-linear unconfined flow situations. | |
MGO: Modular Groundwater Optimizer (Zheng and Wang, 2003) based on MODFLOW and the MT3DMS code (Zheng and Wang, 1999) for contaminant transport simulation | ● Performs optimization using heuristic global optimization methods, including Genetic Algorithm (GA) and Tabu Search (TS). |
● Tightly integrated to the MODFLOW and MT3DMS codes. | |
● Computationally burdensome and cumbersome to use even for relatively straightforward practical situations. | |
SOMOS: Simulation/Optimization Modeling System (Peralta, 2004) | ● Performs optimization using a combination of GA, TS, and Artificial Neuron Network (ANN) in conjunction with groundwater flow and solute transport modeling. |
SEA: Successive Equimarginal Approach, a hybrid of the gradient-based method and the deterministic heuristic-based method (Guo, et al., 2007) | ● Performs optimization using SEA to alleviate some of the computational burden of MGO. |
● Integrated with MODFLOW and MT3DMS. | |
● Cumbersome to use requires frequent user intervention and may not lead to a global optimum. |