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OVERVIEW OF HEURISTIC OPTIMIZATION

Florida International University Department of Civil and Environmental EngineeringOptimization in Water Resources Engineering, Spring 2020 Arturo S. Leon, , , OF HEURISTIC OPTIMIZATIONOPTIMIZATION CLASSIFICATION (Recap)LocalMulti-ObjectiveUn-Constraine dNon-GradientGradient BasedConstrainedSingle-ObjectiveGlobalLI MITATIONS OF DESCENT METHODS Descent methodprocedure is efficient when theobjective functionFisuni-modular(one local optimum only). In caseFismulti-modular, not easy to get out of the neighborhood oflocaloptimumF(X)XF(X)XREASONS FOR HEURISTIC searchHEURISTIC METHODS INTRODUCTION HEURISTIC methods, asnon-gradient methods,do not require anyderivatives of the objective function in order to calculate theoptimum, they are also known as black box methods.

OPTIMIZATION (Eberhart Kennedy -1995) A robust stochastic optimization technique inspired by the social behavior of swarms of insects or flocks of birds –maximize “food”. Apply the concept of social interaction to problem solving. Developed in 1995 by James Kennedy (social-psychologist) and Russell Eberhart (electrical engineer).

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