The analysis of expected fitness and success ratio of two heuristic optimizations on two bimodal MaxSAT problems
AbstractHeuristic algorithms, especially hill-climbing algorithms, are prone to being trapped by local optimization. Many researchers have focused on analyzing convergence and runtime of some heuristic algorithms on SAT-solving problems. However, there is rare work on analyzing success ratio (the ratio of the number of runs that find the global maxima of optimization versus the total runs) and expected fitness at each generation. Expected fitness at each generation could lead us to better understand the expected fitness of a heuristic algorithm could find on the problem to be solve at a certain generation. Success ratio help us understand with what a probability a heuristic algorithm could find the global optimization of the problem to be solved. So, this paper analyzed expected fitness and success ratio of two hill-climbing algorithms on two bimodal MaxSAT problems by using Markov chain. The theoretical and experimental results showed that though hill-climbing algorithms (both hill-climbing RandomWalk and Local (1+1)EA) converged faster, they could not always find global maxima of bimodal SAT-solving problems. The success ratios of hill-climbing algorithms usually have their own limits. The limit of success ratio is dependent on the SAT-solving problem itself and the expected distribution of initial bit string, and independent on whether hill-climbing RandomWalk or Local (1+1)EA is used. Copyright Springer Science+Business Media, LLC. 2012
Download InfoIf you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
Bibliographic InfoArticle provided by Springer in its journal Journal of Global Optimization.
Volume (Year): 54 (2012)
Issue (Month): 4 (December)
Contact details of provider:
Web page: http://www.springer.com/business/operations+research/journal/10898
You can help add them by filling out this form.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Guenther Eichhorn) or (Christopher F Baum).
If references are entirely missing, you can add them using this form.