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Titlebook: Evolutionary Computation in Combinatorial Optimization; 11th European Confer Peter Merz,Jin-Kao Hao Conference proceedings 2011 Springer Be

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11#
發(fā)表于 2025-3-23 11:08:29 | 只看該作者
E. Millich,J. P. Joulia,D. Van Asseltpsack problem. A local search algorithm that explores this property is then proposed and its performance is compared against exact algorithms in terms of running time and number of optimal solutions found. The experimental results indicate that this simple local search algorithm is able to find a re
12#
發(fā)表于 2025-3-23 14:23:02 | 只看該作者
13#
發(fā)表于 2025-3-23 21:04:09 | 只看該作者
Data Retention in the Czech Republicatic programming (UBQP) problem as a case study. In particular, we provide insights as to why one particular variable fixing and scoring strategy leads to better computational results than another one. For this purpose, we perform two investigations, the first analyzing deviations from the best know
14#
發(fā)表于 2025-3-24 00:05:43 | 只看該作者
https://doi.org/10.1007/978-94-017-1484-6ducing the environmental pollution. In this work, we present an evolutionary multiobjective route planning algorithm for solving the route planning problem in the dynamic multi-hop ridesharing. The experiments indicate that the evolutionary approach is able to provide a good quality set of route pla
15#
發(fā)表于 2025-3-24 04:35:18 | 只看該作者
The Mexx Group: Textbook Innovation at Workdreds of processors. We choose as basic constraint solving algorithm for these experiments the ”adaptive search” method, an efficient sequential local search method for Constraint Satisfaction Problems. The implemented algorithm is a parallel version of adaptive search in a multiple independent-walk
16#
發(fā)表于 2025-3-24 10:20:23 | 只看該作者
17#
發(fā)表于 2025-3-24 12:01:59 | 只看該作者
18#
發(fā)表于 2025-3-24 17:46:50 | 只看該作者
19#
發(fā)表于 2025-3-24 22:16:26 | 只看該作者
Daniel Le Métayer,Julien Le Clainche whose candidate solutions are very expensive to evaluate. Because of the inherent spatial intuition behind these models, they are naturally suited to continuous problems but they do not seem applicable to combinatorial problems except for the special case when solutions are naturally encoded as int
20#
發(fā)表于 2025-3-25 03:13:11 | 只看該作者
Tom Dyson,Theodore Konstadinidesificantly reduce the computational time of the solution search space exploration, this latter cost remains exorbitant when very large problem instances are to be solved. As a result, the use of graphics processing units (GPU) has been recently revealed as an efficient way to accelerate the search pr
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