Abstract
For the global optimization problems with continuous variables, evolutionary algorithms (EAs) are often used to find the approximate solutions. The number of generations for an EA to find the approximate solutions, called the first hitting time, is an important index to measure the performance of the EA. However, calculating the first hitting time is still difficult in theory. This paper proposes some new drift conditions that are used to estimate the upper bound of the first hitting times of EAs for finding the approximate solutions. Two case studies are given to show how to apply these conditions to estimate the first hitting times.
Original language | English |
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Pages (from-to) | 37-50 |
Number of pages | 13 |
Journal | International Journal of Computer Mathematics |
Volume | 88 |
Issue number | 1 |
Early online date | 02 Dec 2010 |
DOIs | |
Publication status | Published - 01 Jan 2011 |
Keywords
- complexity theory
- evolutionary algorithm
- global optimization
- approximate solutions
- first hitting time