Titlebook: Applications of Evolutionary Computing; EvoWorkshops 2004: E Günther R. Raidl,Stefano Cagnoni,Giovanni Squiller Conference proceedings 2004

CRACY

Reference work 2016Latest editiontion from the project area by operating directly with a grid of geographically dispersed demand points. Computational results show this to be a promising technique for partitioning the project area and positioning the control switches. Tests were realized with real instances taken from large areas in the city of S?o Paulo.

ANTI

scoliosis

An Improved Genetic Algorithm for the Sequencing by Hybridization Problemd algorithm in the literature. The improvement is achieved by modifying the crossover operator towards an almost deterministic greedy crossover which makes the algorithm both more effective and more efficient. Experimental results on real DNA data are presented to show the advantages of using the proposed algorithm.

潛移默化

Discrete Branch Length Representations for Genetic Algorithms in Phylogenetic Searchetic trees. We find that discretizing the edge lengths changes the fundamental character of the search and can produce higher quality trees. Our results suggest a search that is more robust to traps in local optima and an opportunity to better control the balance between topology search and edge length search.

sperse

偽善

A Genetic Algorithm for Telecommunication Network Designtion from the project area by operating directly with a grid of geographically dispersed demand points. Computational results show this to be a promising technique for partitioning the project area and positioning the control switches. Tests were realized with real instances taken from large areas in the city of S?o Paulo.

Charitable

A Scenario-Based Approach to Protocol Design Using Evolutionary Techniqueseduces to evolving finite-state machines with the specified input/output behaviors. The proposed approach does not overgeneralize the entity behavior producing, by construction, minimal, deterministic and completely specified finite-state machines.

Bouquet

Evolutionary Search of Thresholds for Robust Feature Set Selection: Application to the Analysis of Mfeature subset selection problem. We address this problem using an evolutionary algorithm that learns the appropriate value of the thresholds. The empirical evaluation shows that robust subset of genes can be obtained. This evaluation is done using real data corresponding to the gene expression of lymphomas.

思想靈活

anus928

Evolutionary Algorithms for Optimal Control in Fed-Batch Fermentation Processesmes and using real-valued representations is proposed that is capable of simultaneously optimizing the aforementioned aspects. Outstanding productivity levels were achieved and the results are validated by practice.