Optimización estocástica
Investigación de operaciones Tercera entrega
- Video:Programación estocástica, modelado y teoría. Lección 1
- Fuente:Canal PreMoLab / YouTube
Stochastic optimization of bose-einstein condensation using a genetic algorithm
Optimización estocástica de bose-einstein condensación usando un algoritmo genético
Los algoritmos de optimización estocástica se han convertido en herramientas esenciales para resolver un amplio intervalo de problemas de optimización difíciles y críticos. Tales métodos son capaces de hallar la solución óptima con elementos de incertidumbre o incorporar de modo algorítmico la incertidumbre para abordar un problema determinístico. En este libro se discuten aspectos teóricos de varios de estos algoritmos y cubre su aplicación en diversos campos científicos.
El documento está compuesto por las siguientes partes:
- Stochastic Optimization of Bose-Einstein Condensation Using a Genetic Algorithm
- Theoretical Model of the Physical System: Optimization by the Genetic Algorithm
- Electromagnetic Device Optimization with Stochastic Methods
- Stochastic Approach to Test Pattern Generator Design
- Optimal Design and Placement of Piezoelectric Actuators using Genetic Algorithm: Application to Switched Reluctance Machine Noise Reduction
- Optimal Decision-Making under Uncertainty - Application to Power Transmission Investments
- Research on Network Tomography Measurement Technique
- Stochastic Optimization Over Correlated Data Set: A Case Study on VLSI Decoupling Capacitance Budgeting
- Joint State and Parameter Estimation in Particle Filtering and Stochastic Optimization
- Integral Optimization of the Container Loading Problem
- Understanding Protein-Ligand Interactions Using Simulated Annealing in Dimensionally Reduced Fingerprint Representation
- Comparison among Different Sale-Bidding Strategies to Hedge against Risk in a Multi-Market Environment
- Chance Constrained Programming and Its Applications to Energy Management
- Highway Transportation Project Evaluation and Selection Incorporating Risk and Uncertainty
- Global Optimization of Conventional and Holey Double-Clad Fibres by Stochastic Search
- Global and Dynamic Optimization using the Artificial Chemical Process Paradigm and Fast Monte Carlo Methods for the Solution of Population Balance Models
- Parameter Optimization for Simulating Runoff from Highlatitude River Basins Using Land Surface Model and Global Data Sets
- Evaluation of Stochastic Global Optimization Methods in the Design of Complex Distillation Configurations
- Phase Equilibrium Modeling in Non-Reactive Systems Using Harmony Search.
