Titlebook: Evolutionary Computation in Combinatorial Optimization; 5th European Confere Günther R. Raidl,Jens Gottlieb Conference proceedings 2005 Spr

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,, a New Evolutionary Approach to Graph Generation,ssover and mutation operators are defined in order to evolve such structure. The developed system has been tested on a wireless network configuration and the results compared with those obtained by a genetic programming based approach recently proposed in the literature.

yohimbine

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The Use of Meta-heuristics to Solve Economic Lot Scheduling Problem,f experiment study is used. Two Neighborhood Search heuristics that differ in rounding off scheme of the production frequencies are also tested. Experimental study shows that both tabu search and simulated annealing algorithms outperform two best known solution methods – Dobson’s Heuristic and Hybrid Genetic Algorithm.

撫育

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https://doi.org/10.1007/978-0-230-59779-2el landscape of PSP, so to properly explore the search space. The designed IA shows its ability to tackle standard benchmarks instances substantially better than other IA’s. In particular, for the 3D HP model the IA allowed us to find energy minima not found by other evolutionary algorithms described in literature.

一夫一妻制

Brendan Brown,Philippe Simonnot. The real size test problems, based on the data taken from the production control system, are presented for assessment of the proposed algorithms. The obtained results show that the genetic algorithm with two repair functions can generate good suboptimal solutions in the time, which can be acceptable from the decision maker point of view.

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lf-adaptation of some evolutionary parameters of genetic algorithms (GAs). Here we intend to propose a flexible GA-based algorithm where only few parameters have to be defined by the user. Benchmark problems of combinatorial optimization were used to test the performance of the proposed approach.

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András Kovács,Anikó Horváth,Zsuzsanna Vidrauristics. Some new theoretical improvements not present in early algorithms are now introduced. An application for pattern sequencing problems is examined with new improved computational results. The method is also compared against other approaches, using benchmark instances taken from the literature.

堅(jiān)毅

On the Application of Evolutionary Algorithms to the Consensus Tree Problem,hms are evaluated on a benchmark composed of phylogenetic trees computed from genomic data. The GP-like algorithm is shown to provide better results than the other evolutionary algorithms, and than two greedy heuristics defined . for this problem.