A hybrid genetic algorithm for multiobjective problems with activity analysis-based local search
AbstractThe 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.
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Bibliographic InfoArticle provided by Elsevier in its journal European Journal of Operational Research.
Volume (Year): 193 (2009)
Issue (Month): 1 (February)
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Web page: http://www.elsevier.com/locate/eor
Activity analysis Data envelopment analysis Genetic algorithms Multiple criteria analysis Parallel computing;
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