Abstract
This chapter deals with some simple convergence results related to the parametric optimization methods discussed in Chapter 7. The main idea underlying “convergence analysis” of a method is to identify (mathematically) the solution to which the method converges. Hence to prove that an algorithm works, one must show that the algorithm converges to the optimal solution. In this chapter, this is precisely what we will attempt to do with some algorithms of Chapter 7.
It is truth very certain that, when it is not in our power to determine what is true, we ought to follow what is most probable.
— René Descartes (1596–1650)
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© 2003 Springer Science+Business Media New York
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Gosavi, A. (2003). Convergence Analysis of Parametric Optimization Methods. In: Simulation-Based Optimization. Operations Research/Computer Science Interfaces Series, vol 25. Springer, Boston, MA. https://doi.org/10.1007/978-1-4757-3766-0_12
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DOI: https://doi.org/10.1007/978-1-4757-3766-0_12
Publisher Name: Springer, Boston, MA
Print ISBN: 978-1-4419-5354-4
Online ISBN: 978-1-4757-3766-0
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