A Clustering-Based Model-Building EA for Optimization Problems with Binary and Real-Valued Variables

We propose a novel clustering-based model-building evolutionary algorithm to tackle optimization problems that have both binary and real-valued variables. The search space is clustered every generation using a distance metric that considers binary and real-valued variables jointly in order to capture and exploit dependencies between variables of different types. After clustering, linkage learning takes place within each cluster to capture and exploit dependencies between variables of the same type. We compare this with a model-building approach that only considers dependencies between variables of the same type. Additionally, since many real-world problems have constraints, we examine the use of different well-known approaches to handling constraints: constraint domination, dynamic penalty and global competitive ranking. We experimentally analyze the performance of the proposed algorithms on various unconstrained problems as well as a selection of well-known MINLP benchmark problems that all have constraints, and compare our results with the Mixed-Integer Evolution Strategy (MIES). We find that our approach to clustering that is aimed at the processing of dependencies between binary and real-valued variables can significantly improve performance in terms of required population size and function evaluations when solving problems that exhibit properties such as multiple optima, strong mixed dependencies and constraints

Trans1catheter mitral valve replacement with the NaviGate stent in a preclinical model

Aims: The aim of this study was to test the feasibility of transcatheter mitral valve implantation of the NaviGate device in acute and chronic preclinical models. Methods and results: We evaluated NaviGate valved stent implantation in the mitral position in an acute swine model (n=24, 645 days) through three different approaches - transatrial, transapical, and transseptal - and in a chronic swine model (n=12, >10 days) through a transatrial approach. The NaviGate implantation procedures were successful in 83% of the acute model studies (n=20) and 83% of the chronic model studies (n=10). Echocardiographic assessment showed low gradient across the valved stent (mean gradient <3 mmHg) and the left ventricular outflow tract (mean gradient <6 mmHg). Post implantation, there was no mitral regurgitation (MR) in 75% (n=15) of the acute studies and mild MR in 25% (n=5). In the chronic model, there was no MR in 60% (n=6) and mild MR in 40% (n=4). The implantation procedure was aborted in four acute studies due to inferior vena cava injury and in two chronic studies due to prosthesis-annulus mismatch. Conclusions: In preparation for clinical application, transcatheter mitral implantation of the NaviGate valved stent was proved feasible in acute and chronic preclinical models. The three featured delivery approaches are of particular value for high-risk patients with functional MR and challenging vascular access