Open Access
2014 Combining Interval Branch and Bound and Stochastic Search
Dhiranuch Bunnag
Abstr. Appl. Anal. 2014: 1-15 (2014). DOI: 10.1155/2014/861765


This paper presents global optimization algorithms that incorporate the idea of an interval branch and bound and the stochastic search algorithms. Two algorithms for unconstrained problems are proposed, the hybrid interval simulated annealing and the combined interval branch and bound and genetic algorithm. The numerical experiment shows better results compared to Hansen’s algorithm and simulated annealing in terms of the storage, speed, and number of function evaluations. The convergence proof is described. Moreover, the idea of both algorithms suggests a structure for an integrated interval branch and bound and genetic algorithm for constrained problems in which the algorithm is described and tested. The aim is to capture one of the solutions with higher accuracy and lower cost. The results show better quality of the solutions with less number of function evaluations compared with the traditional GA.


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Dhiranuch Bunnag. "Combining Interval Branch and Bound and Stochastic Search." Abstr. Appl. Anal. 2014 1 - 15, 2014.


Published: 2014
First available in Project Euclid: 27 February 2015

zbMATH: 07023215
MathSciNet: MR3285161
Digital Object Identifier: 10.1155/2014/861765

Rights: Copyright © 2014 Hindawi

Vol.2014 • 2014
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