Numerical and Evolutionary Optimization - Neo 2017

ISBN-13: 9783030071448 / Angielski / Miękka / 2018 / 312 str.

Leonardo Trujillo; Oliver Schutze; Yazmin Maldonado

Spis treści

Deterministic Parameter Control in Differential Evolution with Combined Variants for Constrained Search Spaces.- A Descent Method for Equality and Inequality Constrained Multiobjective Optimization Problems.- Evaluating Memetic Building Spatial Design Optimisation Using Hypervolume Indicator Gradient Ascent.- Fitting Multiple Ellipses with PEARL and a Multi-objective Genetic Algorithm.- Analyzing Evolutionary Art Audience Interaction by Means of a Kinect Based Non-Intrusive Method.- Applying Control Theory to Optimize the Inventory Holding Costs in Supply Chains.- On the Selection of Tuning Parameters in Predictive Controllers Based on NSGA-II.- IDA-PBC Controller Tuning Using Steepest Descent.- Self-Tuning for a SISO-Type Fuzzy Control Based on the Relay Feedback Approach.- Optimal Design Of Sliding Mode Control Combined with Positive Position Feedback.- Biot’s Parameters Estimation In Ultrasound Propagation Through Cancellous Bone.- Optimal Sizing of Low-DropOut Voltage Regulators by NSGA-II and PVT Analysis.- Genetic Optimization of Fuzzy Systems for the Classification of Treated Water Quality.- Stabilization Based on Fuzzy System for Structures Affected by External Disturbances.- Comparison of Two Methods for I/Q Imbalance Compensation Applied in RF Power Amplifiers.- An Application of Data Envelopment Analysis to the Performance Assessment of Online Social Networks Usage in Mazatlan Hotel Organizations. 

Blurb

This book features 15 chapters based on the Numerical and Evolutionary Optimization (NEO 2017) workshop, held from September 27 to 29 in the city of Tijuana, Mexico. The event gathered researchers from two complimentary fields to discuss the theory, development and application of state-of-the-art techniques to address search and optimization problems. The lively event included 7 invited talks and 64 regular talks covering a wide range of topics, from evolutionary computer vision and machine learning with evolutionary computation, to set oriented numeric and steepest descent techniques. Including research submitted by the NEO community, the book provides informative and stimulating material for future research in the field.