Abstract
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.
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© 2010 Springer Science+Business Media, LLC
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Hendrix, E.M.T., G.-Tóth, B. (2010). Goodness of optimization algorithms. In: Introduction to Nonlinear and Global Optimization. Springer Optimization and Its Applications, vol 37. Springer, New York, NY. https://doi.org/10.1007/978-0-387-88670-1_4
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DOI: https://doi.org/10.1007/978-0-387-88670-1_4
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Publisher Name: Springer, New York, NY
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Online ISBN: 978-0-387-88670-1
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