ADAPTIVE HYBRID GENETIC ALGORITHM FOR GROUNDWATER REMEDIATION DESIGN

Genetic algorithms allow solution of more complex non-linear problems than traditional gradient-based approaches, but they are more computationally intensive. One way to improve performance is through inclusion of local search, creating a hybrid genetic algorithm (HGA). This paper presents a new self-adaptive HGA (SAHGA) and compares its performance to a nonadaptive hybrid genetic algorithm (NAHGA) and the simple genetic algorithm (SGA) on a groundwater remediation problem.