The optimal regression testing problem is one of determining the minimum number of test cases needed for revalidating modified software in the maintenance phase. We present two natural optimization algorithms, namely, a simulated annealing and a genetic algorithm, for solving this problem. The algor
Solving structural optimization problems with genetic algorithms and simulated annealing
✍ Scribed by Salvador Botello; Jose L. Marroquin; Eugenio Oñate; Johan Van Horebeek
- Publisher
- John Wiley and Sons
- Year
- 1999
- Tongue
- English
- Weight
- 142 KB
- Volume
- 45
- Category
- Article
- ISSN
- 0029-5981
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✦ Synopsis
In this paper we study the performance of two stochastic search methods: Genetic Algorithms and Simulated Annealing, applied to the optimization of pin-jointed steel bar structures. We show that it is possible to embed these two schemes into a single parametric family of algorithms, and that optimal performance (in a parallel machine) is obtained by a hybrid scheme. Examples of applications to the optimization of several real steel bar structures are presented.
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