Artificial Evolution: 4th European Conference, AE'99 by Cyril Fonlupt, Jin-Kao Hao, Evelyne Lutton, Edmund Ronald,
By Cyril Fonlupt, Jin-Kao Hao, Evelyne Lutton, Edmund Ronald, Marc Schoenauer
The lawsuits of the 4th ecu convention on man made Evolution, AE '99, held in Dunkerque, France, November 3-5, 1999. the various significant subject matters mentioned on the convention contain genetic operators and theoretical versions, functions, brokers and cooperation, and heuristics. Softcover.
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Additional info for Artificial Evolution: 4th European Conference, AE'99 Dunkerque, France, November 3-5, 1999 Selected Papers
C. Hsu. Applying the Genetic Approach to Simulated Annealing in Solving Some NP-Hard Problems. IEEE Transactions on Systems, Man, and Cybernetics. Volume 23, No. 6, 1752 – 1767, 1993 A. Løkketangen. A Comparison of a Genetic Algorithm and a Tabu Search Method for 0/1 Multidimensional Knapsack Problems. In Proceedings of the Nordic Operations Research Conference, 1995 Z. Michalewicz and J. Arabas. Genetic Algorithms for the 0/1 Knapsack Problem. In Z. W. Ra´s and Z. ), Proceedings of the 8th International Symposium on Methodologies for Intelligent Systems, 134 – 143, Lecture Notes in Artificial Intelligence, Volume 869, Springer, 1994 H.
Among the approaches which optimize all individuals, the influence of the initialization is negligible for all ph . Generally, a similar duplicate ratio for both C∗ and R∗ is achieved for LP optimum (LPO) based approaches, while in the case of pseudo-utility ratio (PUR) ordering R∗ produces more duplicates than C∗ . Higher ph values cause a higher duplicate ratio, because a frequent use of the ordering heuristic restricts the search to promising items, which raises the probability to produce good but already existing solutions.
On the Effectivity of Evolutionary Algorithms 27 While all unfeasible individuals are repaired, the feasible solutions are improved by the optimization method, which ensures reaching the boundary B and is applied with a low probability. Thiel and Voss reported worse results for higher probabilities, which might be caused by a loss of diversity due to the optimization heuristic. They also proposed a hybridization with tabu search, which improved the obtained quality but caused significant higher CPU times.