Goodness of optimization algorithms

  • Eligius M. T. HendrixEmail author
  • Boglárka G.-Tóth
Part of the Springer Optimization and Its Applications book series (SOIA, volume 37)


In this chapter, several criteria are discussed to measure the effectiveness and efficiency of algorithms. Moreover, examples of basic algorithms are analyzed. Global Optimization (GO) concepts such as region of attraction, level set, probability of success and performance graph are introduced. To investigate optimization algorithms, we should say what we mean by them in this book; an algorithm is a description of steps, preferably implemented into a computer program, which finds an approximation of an optimum point. The aims can be several: reach a local optimum point, reach a global optimum point, find all global optimum points, reach all global and local optimum points. In general, an algorithm generates a series of points x k that approximate an optimum point.


Local Search Global Optimization Minimum Point Optimum Point Success Region 
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 2010

Authors and Affiliations

  1. 1.Department of Computer ArchitectureMálaga UniversityMálagaSpain
  2. 2.Department of Differential EquationsBudapest University of Technology and EconomicsBudapestHungary

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