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Multi-dimensional Control Problems = Robust Approach /
Record Type:
Language materials, printed : Monograph/item
Title/Author:
Multi-dimensional Control Problems/ by Anurag Jayswal, Preeti, Savin Treanţӑ.
Reminder of title:
Robust Approach /
Author:
Jayswal, Anurag.
other author:
Preeti.
Description:
XV, 186 p. 1 illus.online resource. :
Contained By:
Springer Nature eBook
Subject:
System theory. -
Online resource:
https://doi.org/10.1007/978-981-19-6561-6
ISBN:
9789811965616
Multi-dimensional Control Problems = Robust Approach /
Jayswal, Anurag.
Multi-dimensional Control Problems
Robust Approach /[electronic resource] :by Anurag Jayswal, Preeti, Savin Treanţӑ. - 1st ed. 2022. - XV, 186 p. 1 illus.online resource. - Industrial and Applied Mathematics,2364-6845. - Industrial and Applied Mathematics,.
Preface -- Glossary of Notations -- Chapter 1. Introduction -- Chapter 2. Multi-dimensional Variational Control Problem with Data Uncertainty in Objective Functional -- Chapter 3. Multi-dimensional Variational Control Problem with Data Uncertainty in Constraint Functionals -- Chapter 4. Multi-dimensional Variational Control Problem with Data Uncertainty in Objective and Constraint Functionals -- Chapter 5. The Modified Approach for Multi-dimensional Optimization Problem with Data Uncertainty -- Chapter 6. Semi-infinite Multi-dimensional Variational Control Problem with Data Uncertainty -- Chapter 7. Robust Duality for Multi-dimensional Variational Control Problem with Data Uncertainty -- Chapter 8. On a Class of Second-order PDE&PDI Constrained Robust Optimization Problems -- Bibliography.
This book deals with several types of multi-dimensional control problems in the face of data uncertainty for vector cases—multi-dimensional multi-objective control problem with uncertain objective functionals, uncertain constraint functionals, and uncertain objective as well as constraint functionals, uncertain multi-dimensional multi-objective control problem with semi-infinite constraints, uncertain dual multi-dimensional multi-objective variational control problem, and second-order PDE&PDI constrained robust optimization problem. The book provides the solution approaches—an exact l1 penalty function approach, modified objective approach, robust approach—in the simplest way to solve the recent developing optimization problems in the sense of uncertainty. .
ISBN: 9789811965616
Standard No.: 10.1007/978-981-19-6561-6doiSubjects--Topical Terms:
566168
System theory.
LC Class. No.: Q295
Dewey Class. No.: 003
Multi-dimensional Control Problems = Robust Approach /
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Preface -- Glossary of Notations -- Chapter 1. Introduction -- Chapter 2. Multi-dimensional Variational Control Problem with Data Uncertainty in Objective Functional -- Chapter 3. Multi-dimensional Variational Control Problem with Data Uncertainty in Constraint Functionals -- Chapter 4. Multi-dimensional Variational Control Problem with Data Uncertainty in Objective and Constraint Functionals -- Chapter 5. The Modified Approach for Multi-dimensional Optimization Problem with Data Uncertainty -- Chapter 6. Semi-infinite Multi-dimensional Variational Control Problem with Data Uncertainty -- Chapter 7. Robust Duality for Multi-dimensional Variational Control Problem with Data Uncertainty -- Chapter 8. On a Class of Second-order PDE&PDI Constrained Robust Optimization Problems -- Bibliography.
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This book deals with several types of multi-dimensional control problems in the face of data uncertainty for vector cases—multi-dimensional multi-objective control problem with uncertain objective functionals, uncertain constraint functionals, and uncertain objective as well as constraint functionals, uncertain multi-dimensional multi-objective control problem with semi-infinite constraints, uncertain dual multi-dimensional multi-objective variational control problem, and second-order PDE&PDI constrained robust optimization problem. The book provides the solution approaches—an exact l1 penalty function approach, modified objective approach, robust approach—in the simplest way to solve the recent developing optimization problems in the sense of uncertainty. .
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