3 edition of **Semi-infinite programming** found in the catalog.

- 78 Want to read
- 30 Currently reading

Published
**1979**
by Springer-Verlag in Berlin, New York
.

Written in English

- Mathematical optimization -- Congresses.,
- Maxima and minima -- Congresses.,
- Inequalities (Mathematics) -- Congresses.

**Edition Notes**

Includes bibliographies.

Statement | edited by R. Hettich. |

Series | Lecture notes in control and information sciences ;, 15 |

Contributions | Hettich, R. |

Classifications | |
---|---|

LC Classifications | QA402.5 .S43 |

The Physical Object | |

Pagination | x, 178 p. : |

Number of Pages | 178 |

ID Numbers | |

Open Library | OL4214636M |

ISBN 10 | 0387094792 |

LC Control Number | 80494232 |

This volume provides an outstanding collection of tutorial and survey articles on semi-infinite programming by leading researchers. While the literature on semi-infinite programming has grown enormously, an up-to-date book on this exciting area of optimization has been sorely lacking. Stein, Oliver & Still, Georg, "On generalized semi-infinite optimization and bilevel optimization," European Journal of Operational Research, Elsevier, vol. (3), pages , November.A. Vaz & Edite Fernandes & M. Gomes, "A sequential quadratic programming with a dual parametrization approach to nonlinear semi-infinite programming," TOP: An Official Journal of the Spanish.

This example shows how to use semi-infinite programming to investigate the effect of uncertainty in the model parameters of an optimization problem. We will formulate and solve an optimization problem using the function fseminf, a semi-infinite programming solver in Optimization Toolbox™. The book is available online via HTML, or downloadable as a PDF. Programming R - This one isn't a downloadable PDF, its a collection of wiki pages focused on R. The book assumes some knowledge of statistics and is focused more on programming so you'll need to have an understanding of the underlying principles.

Semi-infinite programming, duality, discretization and optimality conditionsy Alexander Shapiro* School of Industrial and Systems Engineering, Georgia Institute of Technology, Atlanta, Georgia , USA (Received 3 July ; final version received 4 December ) The aim of this article is to give a survey of some basic theory of semi. Semi-Infinite Programming: Recent Advances (Nonconvex Optimization and Its Applications) (1st Edition) by Miguel Ángel Goberna (Editor), Marco A. López (Editor), Miguel Angel Goberna (Editor), Miguel Ç Ngel Goberna, Marco A. Lopez Hardcover, Pages, Published ISBN / ISBN / Book Edition: 1st Edition.

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Semi-infinite programming (briefly: SIP) is an exciting part of mathematical programming. SIP problems include finitely many variables and, in contrast to finite optimization problems, infinitely many inequality : Rembert Reemtsen.

Semi-infinite programming (SIP) deals with optimization problems in which either the number of decision variables or the number of constraints is finite. This book presents the state of the art in SIP in a suggestive way, bringing the powerful SIP tools close to the potential users in different.

Semi-infinite programming (SIP) deals with optimization problems in which either the number of decision variables or the number of constraints is finite.

This book presents the state of the art in SIP in a suggestive way, bringing the powerful SIP tools close to the potential users in different scientific and technological : Hardcover. Semi-infinite programming is a natural extension of linear pro gramming that allows finitely many variables to appear in infinitely many constraints.

As the papers in this collection will reconfirm, the theoretical and practical manifestations and applications of this prob lem formulation are. Semi-infinite programming (briefly: SIP) is an exciting part of mathematical programming. SIP problems include finitely many variables and, in contrast to finite optimization problems, infinitely many inequality constraints.

Prob lems of this type naturally arise in approximation theory. Semi-infinite programming (briefly: SIP) is an exciting part of mathematical programming. SIP problems include finitely many variables and, in contrast to finite optimization problems, infinitely. This article presents a short introduction to semi-infinite programming (SIP), which over the last two decades has become a vivid research area in mathematical programming with a wide range of.

A semi-inﬁnite programming problem is an optimization problem in which ﬁnitely many variables appear in inﬁnitely many constraints. This model naturally arises in an abundant number of applications in different ﬁelds of mathematics, economics and.

Basic Concepts Semi-infinite programming (SIP) problems are optimization problems in which there is an infinite number of variables or an infinite number of constraints (but not both). A general SIP problem can be formulated as. Semi-infinite programming (briefly: SIP) is an exciting part of mathematical programming.

SIP problems include finitely many variables and, in contrast to finite optimization problems, infinitely many inequality constraints. There, algebraic properties of finite linear programming are brought to bear on duality theory in semi-infinite programming.

Section 7 treats numerical methods based on either discretization or local reduction with the emphasis on the design of superlinearly convergent (SQP-type) by: Semi-Infinite programming, that allows for either infinitely many constraints or infinitely many variables but not both, is a natural extension of ordinary mathematical programming.

There are many. Semi-infinite programming (SIP) deals with optimization problems in which either the number of decision variables or the number of constraints is finite.

This book presents the state of the art in SIP in a suggestive way, bringing the powerful SIP tools close to the potential users in different scientific and technological fields. Available in: -infinite programming (SIP) deals with optimization problems in which either the number of decision variables or the number of Due to COVID, orders may be delayed.

Thank you for your : $ () Understanding linear semi-infinite programming via linear programming over cones. Optimization() Generation of dynamic motions under continuous constraints: Efficient computation using B-Splines and Taylor by: In optimization theory, semi-infinite programming (SIP) is an optimization problem with a finite number of variables and an infinite number of constraints, or an infinite number of variables and a finite number of constraints.

In the former case the constraints are typically parameterized. A linear semi-infinite program is an optimization problem with linear objective functions and linear constraints in which either the number of unknowns or the number of constraints is finite.

The many direct applications of linear semi-infinite optimization (or programming) have prompted considerable and increasing research effort in recent years. Hettich, R & Still, GJSemi-infinite programming: Second order optimality conditions. in CA Floudas & PM Pardalos (eds), Encyclopedia of Optimization.

5, Kluwer Cited by: 2. A semi-infinite programming problem is an optimization problem in which finitely many variables appear in infinitely many constraints. This model naturally arises in an abundant number of applications in different fields of mathematics, economics and by: Non-Linear Semi-Infinite Programming.

A thesis submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy in Mathematics at the University of Canterbury, by C.

Price. August, University of Canterbury, Christchurch, New Zealand. Home Browse by Title Periodicals SIAM Review Vol. 35, No. 3 Semi-infinite programming: theory, methods, and applications article Semi-infinite programming: theory, methods, and applications.

From the reviews: "This is the first book which exploits the bilevel structure of semi-infinite programming systematically. It highlights topological and structural aspects of general semi-infinite programming, formulates powerful optimality conditions, and gives a Author: Oliver Stein.It will be shown how this rate depends on whether the minimizer is strict of order one or two and on whether the discretization includes boundary points of the index set in a consistent way.

This is done for common and for generalized semi-infinite by: 2.