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| Author: | Östermark, R. |
| Title: | A multipurpose parallel genetic hybrid algorithm for non-linear non-convex programming problems |
| Journal: | European Journal of Operational Research
2004 : JAN, VOL. 152:1, p. 195-214 |
| Index terms: | Mathematical programming Non-linear models Mixed integer programming Algorithms |
| Language: | eng |
| Abstract: | This study presents a new flexible parallel algorithm for non-convex MINLP-problems and difficult neurogenetic problems. The algorithm combines important features of evolutionary computation and classical non-linear optimization. The algorithm was tested on a set of difficult non-linear programming problems, including a complicated non-convex MINLP-problem. The algorithm proved good performance in all cases. Extensive Monte Carlo simulations demonstrate, that the parallel genetic hybrid algorithm (GHA) has a great potential in solving difficult large scale mathematical programming problems. |
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