A hybrid genetic algorithm for multiobjective problems with activity analysis-based local search

The objective of this research was the development of a method that integrated an activity analysis model of profits from production with a biophysical model, and included the capacity for optimization over multiple objectives. We specified a hybrid genetic algorithm using activity analysis as a local search method, and NSGA-II for calculation of the multiple objective Pareto optimal set. We describe a parallel computing approach to computation of the genetic algorithm, and apply the algorithm to evaluation of an input tax to regulate pollution from agricultural production.