Optimal Removal of Heavy Metals Pollutants from Groundwater Using a Real Genetic Algorithm and Finite-Difference Method

Abstract

The purpose of this research is to investigate the capability of a real genetic algorithm (GA) to remove a heavy-metal pollutant plume from an aquifer. The real genetic algorithm has been used in conjunction with proven and accepted finite-difference analysis to reach an efficient solution. It also illustrates the interaction between the real GA optimizer and the finite-difference technique. Two scenarios regarding the well positions, number of wells, pumping rate at each well, and total cost were determined for the purpose. A new system has been developed for removing heavy metals [mercury (Hg) and cadmium (Cd)] from groundwater in a real problem and proved to be optimal. Real-coding GAs proved to be a practical means of optimizing engineering solutions to problems related to groundwater quality management, in particular those involving discontinuous functions. The real GA can be used with accredited finite-difference methods toward an optimal solution. The developed application of a combined simulation-optimization method for cleanup of contamination from a real landfill in a coastal area of Syria can also be used in other water-resource quality applications.