Nonlinear Assignment Problems

Nonlinear Assignment Problems
Author: Panos M. Pardalos
Publisher: Springer Science & Business Media
Total Pages: 317
Release: 2013-03-09
Genre: Computers
ISBN: 1475731558

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Nonlinear Assignment Problems (NAPs) are natural extensions of the classic Linear Assignment Problem, and despite the efforts of many researchers over the past three decades, they still remain some of the hardest combinatorial optimization problems to solve exactly. The purpose of this book is to provide in a single volume, major algorithmic aspects and applications of NAPs as contributed by leading international experts. The chapters included in this book are concerned with major applications and the latest algorithmic solution approaches for NAPs. Approximation algorithms, polyhedral methods, semidefinite programming approaches and heuristic procedures for NAPs are included, while applications of this problem class in the areas of multiple-target tracking in the context of military surveillance systems, of experimental high energy physics, and of parallel processing are presented. Audience: Researchers and graduate students in the areas of combinatorial optimization, mathematical programming, operations research, physics, and computer science.

On Some Nonlinear Assignment Problems

On Some Nonlinear Assignment Problems
Author: Vladyslav Sokol
Publisher:
Total Pages: 117
Release: 2018
Genre:
ISBN:

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Linear assignment problem (commonly referred to as just assignment problem) is a fundamental problem in combinatorial optimization. The goal is to assign n workers to do n jobs so that the linear sum of corresponding costs is minimized. The linear assignment problem is thoroughly studied and has a O(n^3) solution with Hungarian algorithm. Nevertheless, a wide range of applications involving assignments are naturally modeled with more complex objective functions (for example quadratic sum as in quadratic assignment problem), and are much more computationally challenging. In this thesis we discuss our results on the bilinear assignment problem, which generalizes the quadratic assignment problem, and is also motivated by several unique applications. The focus is on computational complexity, solvable special cases, approximations, linearizations as well as local search algorithms and other heuristic approaches for the problem. We also present our results on few applied projects, where modelling the underlying problem as a nonlinear assignment was instrumental.

Computational Issues in High Performance Software for Nonlinear Optimization

Computational Issues in High Performance Software for Nonlinear Optimization
Author: Almerico Murli
Publisher: Springer Science & Business Media
Total Pages: 159
Release: 1997-01-31
Genre: Business & Economics
ISBN: 0792398629

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Computational Issues in High Performance Software for Nonlinear Research brings together in one place important contributions and up-to-date research results in this important area. Computational Issues in High Performance Software for Nonlinear Research serves as an excellent reference, providing insight into some of the most important research issues in the field.

Assignment Problems, Revised Reprint

Assignment Problems, Revised Reprint
Author: Rainer Burkard
Publisher: SIAM
Total Pages: 403
Release: 2012-10-31
Genre: Mathematics
ISBN: 1611972221

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Assignment Problems is a useful tool for researchers, practitioners and graduate students. In 10 self-contained chapters, it provides a comprehensive treatment of assignment problems from their conceptual beginnings through present-day theoretical, algorithmic and practical developments. The topics covered include bipartite matching algorithms, linear assignment problems, quadratic assignment problems, multi-index assignment problems and many variations of these. Researchers will benefit from the detailed exposition of theory and algorithms related to assignment problems, including the basic linear sum assignment problem and its variations. Practitioners will learn about practical applications of the methods, the performance of exact and heuristic algorithms, and software options. This book also can serve as a text for advanced courses in areas related to discrete mathematics and combinatorial optimisation. The revised reprint provides details on a recent discovery related to one of Jacobi's results, new material on inverse assignment problems and quadratic assignment problems, and an updated bibliography.

Nonlinear Optimization and Related Topics

Nonlinear Optimization and Related Topics
Author: Gianni Pillo
Publisher: Springer Science & Business Media
Total Pages: 484
Release: 2013-06-29
Genre: Mathematics
ISBN: 1475732260

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This volume contains the edited texts of the lectures presented at the Workshop on Nonlinear Optimization held in Erice, Sicily, at the "G. Stampacchia" School of Mathematics of the "E. Majorana" Centre for Scientific Culture, June 23 -July 2, 1998. In the tradition of these meetings, the main purpose was to review and discuss recent advances and promising research trends concerning theory, algorithms and innovative applications in the field of Nonlinear Optimization, and of related topics such as Convex Optimization, Nonsmooth Optimization, Variational Inequalities and Complementarity Problems. The meeting was attended by 83 people from 21 countries. Besides the lectures, several formal and informal discussions took place. The result was a wide and deep knowledge of the present research tendencies in the field. We wish to express our appreciation for the active contribution of all the par ticipants in the meeting. Our gratitude is due to the Ettore Majorana Centre in Erice, which offered its facilities and rewarding environment: its staff was certainly instrumental for the success of the meeting. Our gratitude is also due to Francisco Facchinei and Massimo Roma for the effort and time devoted as members of the Organising Committee. We are indebted to the Italian National Research Council, and in particular to the Group on Functional Analysis and its Applications and to the Committees on Engineering Sciences and on Information Sciences and Technolo gies for their financial support. Finally, we address our thanks to Kluwer Academic Publishers for having offered to publish this volume.

Handbook of Combinatorial Optimization

Handbook of Combinatorial Optimization
Author: Ding-Zhu Du
Publisher: Springer Science & Business Media
Total Pages: 395
Release: 2006-08-18
Genre: Business & Economics
ISBN: 0387238301

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This is a supplementary volume to the major three-volume Handbook of Combinatorial Optimization set. It can also be regarded as a stand-alone volume presenting chapters dealing with various aspects of the subject in a self-contained way.

Linear Programs and Related Problems

Linear Programs and Related Problems
Author: Evar D. Nering
Publisher: Academic Press
Total Pages: 618
Release: 1993
Genre: Computers
ISBN: 9780125154406

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This text is concerned primarily with the theory of linear and nonlinear programming, and a number of closely-related problems, and with algorithms appropriate to those problems. In the first part of the book, the authors introduce the concept of duality which serves as a unifying concept throughout the book. The simplex algorithm is presented along with modifications and adaptations to problems with special structures. Two alternative algorithms, the ellipsoidal algorithm and Karmarker's algorithm, are also discussed, along with numerical considerations. the second part of the book looks at specific types of problems and methods for their solution. This book is designed as a textbook for mathematical programming courses, and each chapter contains numerous exercises and examples.

The Quadratic Assignment Problem

The Quadratic Assignment Problem
Author: E. Cela
Publisher: Springer Science & Business Media
Total Pages: 296
Release: 2013-03-14
Genre: Mathematics
ISBN: 1475727879

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The quadratic assignment problem (QAP) was introduced in 1957 by Koopmans and Beckmann to model a plant location problem. Since then the QAP has been object of numerous investigations by mathematicians, computers scientists, ope- tions researchers and practitioners. Nowadays the QAP is widely considered as a classical combinatorial optimization problem which is (still) attractive from many points of view. In our opinion there are at last three main reasons which make the QAP a popular problem in combinatorial optimization. First, the number of re- life problems which are mathematically modeled by QAPs has been continuously increasing and the variety of the fields they belong to is astonishing. To recall just a restricted number among the applications of the QAP let us mention placement problems, scheduling, manufacturing, VLSI design, statistical data analysis, and parallel and distributed computing. Secondly, a number of other well known c- binatorial optimization problems can be formulated as QAPs. Typical examples are the traveling salesman problem and a large number of optimization problems in graphs such as the maximum clique problem, the graph partitioning problem and the minimum feedback arc set problem. Finally, from a computational point of view the QAP is a very difficult problem. The QAP is not only NP-hard and - hard to approximate, but it is also practically intractable: it is generally considered as impossible to solve (to optimality) QAP instances of size larger than 20 within reasonable time limits.

Knapsack Problems

Knapsack Problems
Author: Silvano Martello
Publisher:
Total Pages: 326
Release: 1990-12-14
Genre: Computers
ISBN:

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Here is a state of art examination on exact and approximate algorithms for a number of important NP-hard problems in the field of integer linear programming, which the authors refer to as ``knapsack.'' Includes not only the classical knapsack problems such as binary, bounded, unbounded or binary multiple, but also less familiar problems such as subset-sum and change-making. Well known problems that are not usually classified in the knapsack area, including generalized assignment and bin packing, are also covered. The text fully develops an algorithmic approach without losing mathematical rigor.