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This is the first book that exploits the bi-level structure of semi-infinite programming systematically. It highlights topological and structural aspects of general semi-infinite programming, formulates powerful optimality conditions, which take this structure into account, and gives a conceptually new bi-level solution method. The results are motivated and illustrated by a number of problems from engineering and economics that give rise to semi-infinite models, including (reverse) Chebyshev approximation, minimax problems, robust optimization, design centering, defect minimization problems for operator equations, and disjunctive programming. Audience: The book is suitable for graduate students and researchers in the fields of optimization and operations research.
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, optimal control, and at numerous engineering applications where the model contains at least one inequality constraint for each value of a parameter and the parameter, repre senting time, space, frequency etc., varies in a given domain. The treatment of such problems requires particular theoretical and numerical techniques. The theory in SIP as well as the number of numerical SIP methods and appli cations have expanded very fast during the last years. Therefore, the main goal of this monograph is to provide a collection of tutorial and survey type articles which represent a substantial part of the contemporary body of knowledge in SIP. We are glad that leading researchers have contributed to this volume and that their articles are covering a wide range of important topics in this subject. It is our hope that both experienced students and scientists will be well advised to consult this volume. We got the idea for this volume when we were organizing the semi-infinite pro gramming workshop which was held in Cottbus, Germany, in September 1996.
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. The volume is divided into four parts. Part I reviews the first decade of SIP (1962-1972). Part II analyses convex and generalised SIP, conic linear programming, and disjunctive programming. New numerical methods for linear, convex, and continuously differentiable SIP problems are proposed in Part III. Finally, Part IV provides an overview of the applications of SIP to probability, statistics, experimental design, robotics, optimization under uncertainty, production games, and separation problems. Audience: This book is an indispensable reference and source for advanced students and researchers in applied mathematics and engineering.
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 abundant and significant. This volume presents 20 carefully selected papers that were pre sented at the International Symposium on Semi-Infinite Programming and Applications, The University of Texas at Austin, September 8-10, 1981. A total of 70 papers were presented by distinguished participants from 15 countries. This was only the second international meeting on this topic, the first taking place in Bad Honnef,Federal Republic of Germany in 1978. A proceedings of that conference was organized and edited by Rainer Hettich of the University of Trier and published by Springer Verlag in 1979. The papers in this volume could have been published in any of several refereed journals. It is also probable that the authors of these papers would normally not have met at the same professional society meeting. Having these papers appear under one cover is thus something of a new phenomenon and provides an indication of both the unification and cross-fertilization opportunities that have emerged in this field. These papers were solicited only through the collective efforts of an International Program Committee organized according to the fol lowing research areas.
Upper bounds for finding an [epsilon]-optimal solution and for the distance between an [epsilon]-optimal solution and an optimal solution are given. (4) Applications of the above algorithm to convex programming. First, a certain semi-infinite linear program is solved by this algorithm so as to obtain a feasible solution of a convex program. Then, another semi-infinite linear program is solved by this algorithm so as to obtain an optimal solution of the convex program. In particular, it is shown that for a strongly consistent convex program this algorithm can find a feasible solution after a finite number of iterations."
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. The authors' aim is to communicate the main theoretical ideas and applications techniques of this fascinating area, from the perspective of convex analysis. The four sections of the book cover: * Modelling with primal and dual problems - the primal problem, space of dual variables, the dual problem. * Linear semi-infinite systems - existence theorems, alternative theorems, redundancy phenomena, geometrical properties of the solution set. * Theory of linear semi-infinite programming - optimality, duality, boundedness, perturbations, well-posedness. * Methods of linear semi-infinite programming - an overview of the main numerical methods for primal and dual problems. Exercises and examples are provided to illustrate both theory and applications. The reader is assumed to be familiar with elementary calculus, linear algebra and general topology. An appendix on convex analysis is provided to ensure that the book is self-contained. Graduate students and researchers wishing to gain a deeper understanding of the main ideas behind the theory of linear optimization will find this book to be an essential text.
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. The volume is divided into four parts. Part I reviews the first decade of SIP (1962-1972). Part II analyses convex and generalised SIP, conic linear programming, and disjunctive programming. New numerical methods for linear, convex, and continuously differentiable SIP problems are proposed in Part III. Finally, Part IV provides an overview of the applications of SIP to probability, statistics, experimental design, robotics, optimization under uncertainty, production games, and separation problems. Audience: This book is an indispensable reference and source for advanced students and researchers in applied mathematics and engineering.