An Introduction to Robust Combinatorial Optimization
Author: Marc Goerigk
Publisher: Springer Nature
Published:
Total Pages: 316
ISBN-13: 3031612612
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Local Search in Combinatorial Optimization
Author: Emile H. L. Aarts
Publisher: Princeton University Press
Published: 2003-08-03
Total Pages: 530
ISBN-13: 9780691115221
DOWNLOAD EBOOK1. Introduction -- 2. Computational complexity -- 3. Local improvement on discrete structures -- 4. Simulated annealing -- 5. Tabu search -- 6. Genetic algorithms -- 7. Artificial neural networks -- 8. The traveling salesman problem: A case study -- 9. Vehicle routing: Modern heuristics -- 10. Vehicle routing: Handling edge exchanges -- 11. Machine scheduling -- 12. VLSI layout synthesis -- 13. Code design.
Robust Optimization
Author: Aharon Ben-Tal
Publisher: Princeton University Press
Published: 2009-08-10
Total Pages: 565
ISBN-13: 1400831059
DOWNLOAD EBOOKRobust optimization is still a relatively new approach to optimization problems affected by uncertainty, but it has already proved so useful in real applications that it is difficult to tackle such problems today without considering this powerful methodology. Written by the principal developers of robust optimization, and describing the main achievements of a decade of research, this is the first book to provide a comprehensive and up-to-date account of the subject. Robust optimization is designed to meet some major challenges associated with uncertainty-affected optimization problems: to operate under lack of full information on the nature of uncertainty; to model the problem in a form that can be solved efficiently; and to provide guarantees about the performance of the solution. The book starts with a relatively simple treatment of uncertain linear programming, proceeding with a deep analysis of the interconnections between the construction of appropriate uncertainty sets and the classical chance constraints (probabilistic) approach. It then develops the robust optimization theory for uncertain conic quadratic and semidefinite optimization problems and dynamic (multistage) problems. The theory is supported by numerous examples and computational illustrations. An essential book for anyone working on optimization and decision making under uncertainty, Robust Optimization also makes an ideal graduate textbook on the subject.
A First Course in Combinatorial Optimization
Author: Jon Lee
Publisher: Cambridge University Press
Published: 2004-02-09
Total Pages: 232
ISBN-13: 9780521010122
DOWNLOAD EBOOKA First Course in Combinatorial Optimization is a text for a one-semester introductory graduate-level course for students of operations research, mathematics, and computer science. It is a self-contained treatment of the subject, requiring only some mathematical maturity. Topics include: linear and integer programming, polytopes, matroids and matroid optimization, shortest paths, and network flows. Central to the exposition is the polyhedral viewpoint, which is the key principle underlying the successful integer-programming approach to combinatorial-optimization problems. Another key unifying topic is matroids. The author does not dwell on data structures and implementation details, preferring to focus on the key mathematical ideas that lead to useful models and algorithms. Problems and exercises are included throughout as well as references for further study.
Combinatorial Optimization
Author: Alexander Schrijver
Publisher: Springer Science & Business Media
Published: 2003-02-12
Total Pages: 2024
ISBN-13: 9783540443896
DOWNLOAD EBOOKFrom the reviews: "About 30 years ago, when I was a student, the first book on combinatorial optimization came out referred to as "the Lawler" simply. I think that now, with this volume Springer has landed a coup: "The Schrijver". The box is offered for less than 90.- EURO, which to my opinion is one of the best deals after the introduction of this currency." OR-Spectrum
Recoverable Robustness in Combinatorial Optimization
Author: Christina Büsing
Publisher:
Published: 2011
Total Pages: 154
ISBN-13: 9783869557717
DOWNLOAD EBOOKRobust Discrete Optimization and Its Applications
Author: Panos Kouvelis
Publisher: Springer Science & Business Media
Published: 2013-03-09
Total Pages: 373
ISBN-13: 1475726201
DOWNLOAD EBOOKThis book deals with decision making in environments of significant data un certainty, with particular emphasis on operations and production management applications. For such environments, we suggest the use of the robustness ap proach to decision making, which assumes inadequate knowledge of the decision maker about the random state of nature and develops a decision that hedges against the worst contingency that may arise. The main motivating factors for a decision maker to use the robustness approach are: • It does not ignore uncertainty and takes a proactive step in response to the fact that forecasted values of uncertain parameters will not occur in most environments; • It applies to decisions of unique, non-repetitive nature, which are common in many fast and dynamically changing environments; • It accounts for the risk averse nature of decision makers; and • It recognizes that even though decision environments are fraught with data uncertainties, decisions are evaluated ex post with the realized data. For all of the above reasons, robust decisions are dear to the heart of opera tional decision makers. This book takes a giant first step in presenting decision support tools and solution methods for generating robust decisions in a variety of interesting application environments. Robust Discrete Optimization is a comprehensive mathematical programming framework for robust decision making.
Ant Colony Optimization
Author: Marco Dorigo
Publisher: MIT Press
Published: 2004-06-04
Total Pages: 324
ISBN-13: 9780262042192
DOWNLOAD EBOOKAn overview of the rapidly growing field of ant colony optimization that describes theoretical findings, the major algorithms, and current applications. The complex social behaviors of ants have been much studied by science, and computer scientists are now finding that these behavior patterns can provide models for solving difficult combinatorial optimization problems. The attempt to develop algorithms inspired by one aspect of ant behavior, the ability to find what computer scientists would call shortest paths, has become the field of ant colony optimization (ACO), the most successful and widely recognized algorithmic technique based on ant behavior. This book presents an overview of this rapidly growing field, from its theoretical inception to practical applications, including descriptions of many available ACO algorithms and their uses. The book first describes the translation of observed ant behavior into working optimization algorithms. The ant colony metaheuristic is then introduced and viewed in the general context of combinatorial optimization. This is followed by a detailed description and guide to all major ACO algorithms and a report on current theoretical findings. The book surveys ACO applications now in use, including routing, assignment, scheduling, subset, machine learning, and bioinformatics problems. AntNet, an ACO algorithm designed for the network routing problem, is described in detail. The authors conclude by summarizing the progress in the field and outlining future research directions. Each chapter ends with bibliographic material, bullet points setting out important ideas covered in the chapter, and exercises. Ant Colony Optimization will be of interest to academic and industry researchers, graduate students, and practitioners who wish to learn how to implement ACO algorithms.
Robust Data Mining
Author: Petros Xanthopoulos
Publisher: Springer Science & Business Media
Published: 2012-11-28
Total Pages: 67
ISBN-13: 1441998780
DOWNLOAD EBOOKData uncertainty is a concept closely related with most real life applications that involve data collection and interpretation. Examples can be found in data acquired with biomedical instruments or other experimental techniques. Integration of robust optimization in the existing data mining techniques aim to create new algorithms resilient to error and noise. This work encapsulates all the latest applications of robust optimization in data mining. This brief contains an overview of the rapidly growing field of robust data mining research field and presents the most well known machine learning algorithms, their robust counterpart formulations and algorithms for attacking these problems. This brief will appeal to theoreticians and data miners working in this field.
Operations Research Proceedings 1994
Author: Ulrich Derigs
Publisher: Springer Science & Business Media
Published: 2012-12-06
Total Pages: 593
ISBN-13: 3642794599
DOWNLOAD EBOOKAn insight into the latest results from the world of operations research - a wide-ranging field, as is shown by the book's 24 sections, corresponding to the conference program itself. Although problems of a primarily methodological nature are discussed, the emphasis is placed firmly on practical subjects, such as reports from the fields of healthcare, environmental protection, logistics and traffic engineering. This selection also clearly illustrates the extent to which OR is spreading into and already interwoven in other scientific disciplines.
