Use of Statistical Outlier Detection Method in Adaptive\ud Evolutionary Algorithms

In this paper, the issue of adapting probabilities for Evolutionary Algorithm (EA) search operators is revisited. A framework is devised for distinguishing between measurements of performance and the interpretation of those measurements for purposes of adaptation. Several examples of measurements and statistical interpretations are provided. Probability value adaptation is tested using an EA with 10 search operators against 10 test problems with results indicating that both the type of measurement and its statistical interpretation play significant roles in EA performance. We also find that selecting operators based on the prevalence of outliers rather than on average performance is able to provide considerable improvements to\ud adaptive methods and soundly outperforms the non-adaptive\ud case

Use of statistical outlier detection method in adaptive evolutionary algorithms

In this paper, the issue of adapting probabilities for Evolutionary Algorithm (EA) search operators is revisited. A framework is devised for distinguishing between measurements of performance and the interpretation of those measurements for purposes of adaptation. Several examples of measurements and statistical interpretations are provided. Probability value adaptation is tested using an EA with 10 search operators against 10 test problems with results indicating that both the type of measurement and its statistical interpretation play significant roles in EA performance. We also find that selecting operators based on the prevalence of outliers rather than on average performance is able to provide considerable improvements to adaptive methods and soundly outperforms the non-adaptive case

A Simulated Annealing/Tabu Search Algorithm for the Vehicle Routing Problem

The Vehicle Routing Problem is an NP-complete problem that has been studied extensively since it was introduced in 1958 by G. B. Dantzig and J. H. Ramser. This thesis creates three algorithms that endeavor to find an optimal solution for each problem tested. Two of the algorithms (Simulated Annealing and Tabu Search) have been used previously to solve this problem. These two solution methods are revisited to discover whether a new approach to creating routes will produce the best-known optimal values every time. New routes are created by forming route neighborhoods and then selecting cities from these neighborhoods for insertion. The third algorithm is an original algorithm which combines Simulated Annealing and Tabu Search. The algorithms presented do not produce the best-known optimal values, but are competitive with previously published algorithms

Locating disease genes using Bayesian variable selection with the Haseman-Elston method

BACKGROUND: We applied stochastic search variable selection (SSVS), a Bayesian model selection method, to the simulated data of Genetic Analysis Workshop 13. We used SSVS with the revisited Haseman-Elston method to find the markers linked to the loci determining change in cholesterol over time. To study gene-gene interaction (epistasis) and gene-environment interaction, we adopted prior structures, which incorporate the relationship among the predictors. This allows SSVS to search in the model space more efficiently and avoid the less likely models. RESULTS: In applying SSVS, instead of looking at the posterior distribution of each of the candidate models, which is sensitive to the setting of the prior, we ranked the candidate variables (markers) according to their marginal posterior probability, which was shown to be more robust to the prior. Compared with traditional methods that consider one marker at a time, our method considers all markers simultaneously and obtains more favorable results. CONCLUSIONS: We showed that SSVS is a powerful method for identifying linked markers using the Haseman-Elston method, even for weak effects. SSVS is very effective because it does a smart search over the entire model space

Prospect for the Higgs searches with the ATLAS detector

The investigation of the electroweak symmetry breaking is one of the primary tasks of the experiments at the CERN Large Hadron Collider (LHC). The potential of the ATLAS experiment for the discovery of the Higgs boson(s) in Standard Model and Minimal Supersymmetric Standard Model is presented, with emphasis on studies which have been completed recently.Comment: Presented at Cracow Epiphany Conference on Hadron Interactions at the Dawn of the LHC, dedicated to memory of J. Kwiecinski, Krakow, Poland, 5-7 January 2009, 22page