Numerical and Evolutionary Optimization – NEO 2017

1. Front Matter

   Pages i-xiv

   PDF

2. Constraint Handling Techniques

   1. Front Matter

      Pages 1-1

      PDF

   2. Deterministic Parameter Control in Differential Evolution with Combined Variants for Constrained Search Spaces

      • Octavio Ramos-Figueroa, María-Margarita Reyes-Sierra, Efrén Mezura-Montes

      Pages 3-28

   3. A Descent Method for Equality and Inequality Constrained Multiobjective Optimization Problems

      • Bennet Gebken, Sebastian Peitz, Michael Dellnitz

      Pages 29-61

   4. Evaluating Memetic Building Spatial Design Optimisation Using Hypervolume Indicator Gradient Ascent

      • Koen van der Blom, Sjonnie Boonstra, Hao Wang, Hèrm Hofmeyer, Michael T. M. Emmerich

      Pages 62-86

3. Evolutionary and Genetic Computation

   1. Front Matter

      Pages 87-87

      PDF

   2. Fitting Multiple Ellipses with PEARL and a Multi-objective Genetic Algorithm

      • Heriberto Cruz Hernández, Luis Gerardo de la Fraga

      Pages 89-107

   3. Analyzing Evolutionary Art Audience Interaction by Means of a Kinect Based Non-intrusive Method

      • Francisco Fernández de Vega, Mario García-Valdez, J. J. Merelo, Georgina Aguilar, Cayetano Cruz, Patricia Hernández

      Pages 108-123

4. Optimal Control

   1. Front Matter

      Pages 125-125

      PDF

   2. Applying Control Theory to Optimize the Inventory Holding Costs in Supply Chains

      • Pablo M. Ayllon-Lorenzo, Selene L. Cardenas-Maciel, Nohe R. Cazarez-Castro

      Pages 127-137

   3. On the Selection of Tuning Parameters in Predictive Controllers Based on NSGA-II

      • R. C. Gutiérrez-Urquídez, G. Valencia-Palomo, O. M. Rodríguez-Elías, F. R. López-Estrada, J. A. Orrante-Sakanassi

      Pages 138-157

   4. IDA-PBC Controller Tuning Using Steepest Descent

      • J. A. Morales, M. A. Castro, D. Garcia, C. Higuera, J. Sandoval

      Pages 158-170

   5. Self-tuning for a SISO-type Fuzzy Control Based on the Relay Feedback Approach

      • Pablo J. Prieto, Nohe R. Cazarez-Castro, Luis T. Aguilar, Selene L. Cardenas-Maciel

      Pages 171-186

   6. Optimal Design of Sliding Mode Control Combined with Positive Position Feedback

      • J. Enríquez-Zárate, L. Trujillo, C. Hernández, Claudia N. Sánchez

      Pages 187-199

5. Real-World Applications

   1. Front Matter

      Pages 201-201

      PDF

   2. Biot’s Parameters Estimation in Ultrasound Propagation Through Cancellous Bone

      • Miguel Angel Moreles, Joaquin Peña, Jose Angel Neria

      Pages 203-224

   3. Optimal Sizing of Low-DropOut Voltage Regulators by NSGA-II and PVT Analysis

      • Jesus Lopez-Arredondo, Esteban Tlelo-Cuautle, Luis Gerardo de la Fraga, Victor Hugo Carbajal-Gomez, Miguel Aurelio Duarte-Villaseñor

      Pages 225-247

   4. Genetic Optimization of Fuzzy Systems for the Classification of Treated Water Quality

      • Itzel G. Gaytan-Reyes, Nohe R. Cazarez-Castro, Selene L. Cardenas-Maciel, David A. Lara-Ochoa, Armando Martinez-Graciliano

      Pages 248-260

   5. Stabilization Based on Fuzzy System for Structures Affected by External Disturbances

      • Marco A. Alcaraz-Rodriguez, Nohe R. Cazarez-Castro, Selene L. Cardenas-Maciel, Luis N. Coria, Sergio Contreras-Hernandez

      Pages 261-274

   6. Comparison of Two Methods for I/Q Imbalance Compensation Applied in RF Power Amplifiers

      • S. A. Juárez-Cázares, E. Allende-Chávez, Y. Sandoval-Ibarra, J. R. Cárdenas-Valdez, E. Tlelo-Cuautle, J. C. Nuñez-Pérez

      Pages 275-294

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.

• Smart Cities
• NEO 2017
• Computational Intelligence
• Numerical Optimization
• Evolutionary Optimization
• Search and Optimization Techniques

• Posgrado en Ciencias de la Ingeniería, Tecnológico Nacional de México - Instituto Tecnológico de Tijuana, Tijuana, Mexico

  Leonardo Trujillo, Yazmin Maldonado, Paul Valle

• Computer Science Department, Cinvestav-IPN, Mexico City, Mexico

  Oliver Schütze

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