................................................................................................................... 14 Area and time restrictions.................................................................................................... 18 Minimum size restrictions..................................................................................................... 19

increases it puts more and more selective pressure on the GA to find a feasible solution. The ideas presented in this paper come from two basic areas: calculus-based nonlinear programming and simulated annealing. The non-stationary penalty methods are tested on four NP test cases and the effectiveness

This paper provides a comprehensive survey of the most popular constraint-handling techniques currently used with evolutionary algorithms. We review approaches that go from simple variations of a penalty function, to others, more sophisticated, that are biologically inspired on emulations

Abstract not found

Twenty years ago, in the pages of the Journal of Common Market Studies, Hedley Bull launched a searing critique of the European Community’s ‘civilian power ’ in international affairs. Since that time the increasing role of the European Union (EU) in areas of security and defence policy has led to a

of our knowledge, these are the first algorithms to perform sparse logistic regression with an Lp and elastic net (Le) penalty. The regularization parameters are decided through maximizing the area under the ROC curve (AUC) of the test data. Experimental results on methylation and microarray data attest

penalty scoring func-tions. We further discuss the applicability of the proposed transformation in re-lated areas, including preference reasoning, collective decision-making and auto-mated negotiation.

The current study sought to test the predictions of attentional control theory (ACT) in a sporting environment. Fourteen experienced footballers took penalty kicks under low- and high-threat counterbalanced conditions while wearing a gaze registration system. Fixations to target locations

for choosing appropriate penalties and evaluate its potential for future monitoring of decisions. Areas for continued attention are identified in the case study, because fully consistent treatment cannot yet be demonstrated.

realtime. For each object, we introduce a penalty based upon distance from a region of interest. This results in a segmentation biased to this area. Also, we demonstrate the use of a track point filter for predicting the location of the object in each frame. The distance penalty is then centered