Titlebook: Parallel Problem Solving from Nature - PPSN V; 5th International Co Agoston E. Eiben,Thomas Bäck,Hans-Paul Schwefel Conference proceedings

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书目名称Parallel Problem Solving from Nature - PPSN V影响因子(影响力)




书目名称Parallel Problem Solving from Nature - PPSN V影响因子(影响力)学科排名




书目名称Parallel Problem Solving from Nature - PPSN V网络公开度




书目名称Parallel Problem Solving from Nature - PPSN V网络公开度学科排名




书目名称Parallel Problem Solving from Nature - PPSN V被引频次




书目名称Parallel Problem Solving from Nature - PPSN V被引频次学科排名




书目名称Parallel Problem Solving from Nature - PPSN V年度引用




书目名称Parallel Problem Solving from Nature - PPSN V年度引用学科排名




书目名称Parallel Problem Solving from Nature - PPSN V读者反馈




书目名称Parallel Problem Solving from Nature - PPSN V读者反馈学科排名

结构

On the optimization of unimodal functions with the (1+1) evolutionary algorithm,ereby we show that unimodal functions can be very difficult to be optimized for the (1+1) EA. Furthermore, we prove that a little modification in the selection method can lead to huge changes in the expected running time.

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atopic

Mutate large, but inherit small! On the analysis of rescaled mutations in (,)-ES with noisy fitness data, progress rate formula is sketched, its predictions are compared with experiments, and its limitations are shown. The dynamical behavior of the ES is investigated. It will be shown that standard self-adaptation has considerable problems to drive the ES in its optimum working regime. Remedies are provided to improve the self-adaptation.

灾祸

Analytic curve detection from a noisy binary edge map using genetic algorithm, Algorithm in combination with the Randomized Hough Transform, along with a different scoring function, to deal with such environments. This approach is also an improvement over random search and in contrast to standard Hough transform algorithms, is not limited to simple curves like straight line or circle.

Genome

Directed

保守

The effect of spin-flip symmetry on the performance of the simple GA,timize deterministically and yet show a wide range of SGA behavior. They have been extensively studied in statistical physics; results from this field explain the negative effect of symmetry on the convergence behavior of the SGA. This note intends to introduce them to the GA-community.

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