Name
Title | ||
|---|---|---|
A Continuous Genetic Algorithm Designed for the Global Optimization of Multimodal Functions |
Abstract | ||
|---|---|---|
Genetic algorithms are stochastic search approaches basedon randomized operators, such as selection, crossover and mutation,inspired by the natural reproduction and evolution of the livingcreatures. However, few published works deal with their applicationto the global optimization of functions depending on continuousvariables.A new algorithm called Continuous Genetic Algorithm (CGA) is proposedfor the global optimization of multiminima functions. In order tocover a wide domain of possible solutions, our algorithm first takescare over the choice of the initial population. Then it locates themost promising area of the solution space, and continues the searchthrough an “intensification” inside this area. The selection, thecrossover and the mutation are performed by using the decimal code.The efficiency of CGA is tested in detail through a set of benchmarkmultimodal functions, of which global and local minima are known. CGAis compared to Tabu Search and Simulated Annealing, as alternativealgorithms. |
Year | DOI | Venue |
|---|---|---|
2000 | 10.1023/A:1009626110229 | J. Heuristics |
Keywords | Field | DocType |
genetic algorithm,global optimization,continuous variables | Continuous optimization,Simulated annealing,Population,Mathematical optimization,Crossover,Global optimization,Meta-optimization,Artificial intelligence,Tabu search,Genetic algorithm,Mathematics,Machine learning | Journal |
Volume | Issue | ISSN |
6 | 2 | 1572-9397 |
Citations | PageRank | References |
87 | 9.38 | 8 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Rachid Chelouah | 1 | 405 | 37.20 |
| Patrick Siarry | 2 | 2490 | 158.54 |