Stochastic Optimization - Seeing the Optimal for the Uncertain

Dritsas, Ioannis

Stochastic Optimization - Seeing the Optimal for the Uncertain

Edited by Ioannis Dritsas

Abstract: Stochastic Optimization Algorithms have become essential tools in solving a wide range of difficult and critical optimization problems. Such methods are able to find the optimum solution of a problem with uncertain elements or to algorithmically incorporate uncertainty to solve a deterministic problem. They even succeed in fighting uncertainty with uncertainty. This book discusses theoretical aspects of many such algorithms and covers their application in various scientific fields.

JEL-codes: C60 (search for similar items in EconPapers)
Date: 2011
ISBN: 978-953-307-829-8
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Book downloadable chapter-by-chapter

Chapters in this book:

Chance Constrained Programming and Its Applications to Energy Management: Wim Van Ackooij, Rene Henrion, Andris Moller and Riadh Zorgati
Comparison among Different Sale-Bidding Strategies to Hedge against Risk in a Multi-Market Environment: Daniele Menniti, Nadia Scordino, Nicola Sorrentino and Antonio Violi
Electromagnetic Device Optimization with Stochastic Methods: Piergorgio Alotto
Evaluation of Stochastic Global Optimization Methods in the Design of Complex Distillation Configurations: Juan Gabriel Segovia-Hernandez, Erick Yair Miranda-Galindo, Julian Cabrera-Ruiz, Salvador Hernandez and Adrian Bonilla-Petriciolet
Global and Dynamic Optimization using the Artificial Chemical Process Paradigm and Fast Monte Carlo Methods for the Solution of Population Balance Models: Roberto Irizarry
Global Optimization of Conventional and Holey Double-Clad Fibres by Stochastic Search: Ioannis Georgiou Dritsas
Highway Transportation Project Evaluation and Selection Incorporating Risk and Uncertainty: Zongzhi Li
Integral Optimization of the Container Loading Problem: Rafael Guillermo Garcia-Caceres, Carlos A. Vega-Mejia and Juan Caballero-Villalobos
Joint State and Parameter Estimation in Particle Filtering and Stochastic Optimization: Xiaojun Yang and Keyi Xing
Optimal Decision-Making under Uncertainty - Application to Power Transmission Investments: Fernando Olsina and Gerardo Blanco
Optimal Design and Placement of Piezoelectric Actuators using Genetic Algorithm: Application to Switched Reluctance Machine Noise Reduction: Javier Ojeda, Xavier Mininger, Mohamed Gabsi and Yongdong Li
Parameter Optimization for Simulating Runoff from Highlatitude River Basins Using Land Surface Model and Global Data Sets: Yeugeniy M. Gusev and Olga N. Nasonova
Phase Equilibrium Modeling in Non-Reactive Systems Using Harmony Search: Adrian Bonilla-Petriciolet, Juan Gabriel Segovia-Hernandez, Didilia I. Mendoza-Castillo and Juan Carlos Tapia-Picazo
Research on Network Tomography Measurement Technique: Yao Ye, Cai Wandong and Li Yongjun
Stochastic Approach to Test Pattern Generator Design: Gregor Papa and Tomasz Garbolino
Stochastic Optimization of Bose-Einstein Condensation Using a Genetic Algorithm: Thorsten Schumm and Wolfgang Rohringer
Stochastic Optimization Over Correlated Data Set: A Case Study on VLSI Decoupling Capacitance Budgeting: Yiyu Shi and Jinjun Xiong
Theoretical Model of the Physical System: Optimization by the Genetic Algorithm: Stanislav Jurecka
Understanding Protein-Ligand Interactions Using Simulated Annealing in Dimensionally Reduced Fingerprint Representation: Ravi K. Nandigam and Sangtae Kim

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Persistent link: https://EconPapers.repec.org/RePEc:ito:pbooks:900

DOI: 10.5772/623

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