Modeling and Solving Real-Life Global Optimization Problems with Meta-heuristic Methods

Part of the Springer Optimization and Its Applications book series (SOIA, volume 25)


Many real-life problems can be modeled as global optimization problems. There are many examples that come from agriculture, chemistry, biology, and other fields. Meta-heuristic methods for global optimization are flexible and easy to implement and they can provide high-quality solutions. In this chapter, we give a brief review of the frequently used heuristic methods for global optimization. We also provide examples of real-life problems modeled as global optimization problems and solved by meta-heuristic methods, with the aim of analyzing the heuristic approach that is implemented.


Objective Function Particle Swarm Optimization Simulated Annealing Differential Evolution Forest Inventory 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer Science+Business Media, LLC 2009

Authors and Affiliations

  1. 1.Center for Applied OptimizationUniversity of FloridaGainesvilleUSA

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