Using genetic algorithms to solve inverse problems

Abstract

Genetic algorithms are globally oriented in searching, and thus potentially useful in solving optimization problems in which the objective function responses contain multiple optima and other irregularities. The usefulness of genetic algorithms in solving inverse problems is investigated in the context of calibrating rainfall-runoff models. A genetic algorithm is introduced and used to calibrate a conceptual rainfall-runoff model with nine parameters. First, a hypothetical example, in which the true optimum set of parameter values was known by assumption, is used to examine whether the genetic algorithm is capable of finding that optimum. Second, real data from four catchments is used to stu..