Inherently Parallel Algorithms in Feasibility and Optimization and their Applications

Etukansi
Elsevier, 18.6.2001 - 516 sivua
The Haifa 2000 Workshop on "Inherently Parallel Algorithms for Feasibility and Optimization and their Applications" brought together top scientists in this area. The objective of the Workshop was to discuss, analyze and compare the latest developments in this fast growing field of applied mathematics and to identify topics of research which are of special interest for industrial applications and for further theoretical study.

Inherently parallel algorithms, that is, computational methods which are, by their mathematical nature, parallel, have been studied in various contexts for more than fifty years. However, it was only during the last decade that they have mostly proved their practical usefulness because new generations of computers made their implementation possible in order to solve complex feasibility and optimization problems involving huge amounts of data via parallel processing. These led to an accumulation of computational experience and theoretical information and opened new and challenging questions concerning the behavior of inherently parallel algorithms for feasibility and optimization, their convergence in new environments and in circumstances in which they were not considered before their stability and reliability. Several research groups all over the world focused on these questions and it was the general feeling among scientists involved in this effort that the time has come to survey the latest progress and convey a perspective for further development and concerted scientific investigations. Thus, the editors of this volume, with the support of the Israeli Academy for Sciences and Humanities, took the initiative of organizing a Workshop intended to bring together the leading scientists in the field. The current volume is the Proceedings of the Workshop representing the discussions, debates and communications that took place. Having all that information collected in a single book will provide mathematicians and engineers interested in the theoretical and practical aspects of the inherently parallel algorithms for feasibility and optimization with a tool for determining when, where and which algorithms in this class are fit for solving specific problems, how reliable they are, how they behave and how efficient they were in previous applications. Such a tool will allow software creators to choose ways of better implementing these methods by learning from existing experience.

 

Sisältö

A LOGQUADRATIC PROJECTION METHOD FOR CONVEX FEASIBILITY PROBLEMS
1
RESULTS AND OPEN PROBLEMS
11
JOINT AND SEPARATE CONVEXITY OF THE BREGMAN DISTANCE
23
A PARALLEL ALGORITHM FOR NONCOOPERATIVE RESOURCE ALLOCATION GAMES
37
ASYMPTOTIC BEHAVIOR OF QUASINONEXPANSIVE MAPPINGS
49
THE OUTER BREGMAN PROJECTION METHOD FOR STOCHASTIC FEASIBILITY PROBLEMS IN BANACH SPACES
69
BREGMANLEGENDRE MULTIDISTANCE PROJECTION ALGORITHMS FOR CONVEX FEASIBILITY AND OPTIMIZATION
87
AVERAGING STRINGS OF SEQUENTIAL ITERATIONS FOR CONVEX FEASIBILITY PROBLEMS
101
GENERIC CONVERGENCE OF ALGORITHMS FOR SOLVING STOCHASTIC FEASIBILITY PROBLEMS
279
SUPERLINEAR RATE OF CONVERGENCE AND OPTIMAL ACCELERATION SCHEMES IN THE SOLUTION OF CONVEX INEQUALITY PR...
297
ALGEBRAIC RECONSTRUCTION TECHNIQUES USING SMOOTH BASIS FUNCTIONS FOR HELICAL CONEBEAM TOMOGRAPHY
307
COMPACT OPERATORS AS PRODUCTS OF PROJECTIONS
325
PARALLEL SUBGRADIENT METHODS FOR CONVEX OPTIMIZATION
335
DIRECTIONAL HALLEY AND QUASIHALLEY METHODS IN N VARIABLES
345
ERGODIC CONVERGENCE TO A ZERO OF THE EXTENDED SUM OF TWO MAXIMAL MONOTONE OPERATORS
369
DISTRIBUTED ASYNCHRONOUS INCREMENTAL SUBGRADIENT METHODS
381

QUASIFEJẺRIAN ANALYSIS OF SOME OPTIMIZATION ALGORITHMS
115
ON THEORY AND PRACTICE OF ROW RELAXATION METHODS
153
RESULTS AND CONJECTURES
187
A BRIEF SURVEY
203
AN OBJECTORIENTED FRAMEWORK FOR PARALLEL BRANCH AND BOUND
219
APPROACHING EQUILIBRIUM IN PARALLEL
267
RANDOM ALGORITHMS FOR SOLVING CONVEX INEQUALITIES
409
PARALLEL ITERATIVE METHODS FOR SPARSE LINEAR SYSTEMS
423
ON THE RELATION BETWEEN BUNDLE METHODS FOR MAXIMAL MONOTONE INCLUSIONS AND HYBRID PROXIMAL POINT ALGOR...
441
THEORY AND PRACTICE
457
THE HYBRID STEEPEST DESCENT METHOD FOR THE VARIATIONAL INEQUALITY PROBLEM OVER THE INTERSECTION OF FIXED P...
473
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Sivu 49 - This research was supported by the Fund for the Promotion of Research at the Technion and by the Technion VPR Fund - L.
Sivu 49 - This research was supported by The Israel Science Foundation founded by the Israel Academy of Sciences and Humanities.
Sivu 21 - AND S. REICH, On the asymptotic behavior of nonexpansive mappings and semigroups in Banach spaces, Houston J.

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