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The Traveling Salesman Problem: A Computational Study (Princeton Series in Applied Mathematics) Kindle Edition

4.8 out of 5 stars 4 customer reviews

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Length: 608 pages
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Editorial Reviews

Review


Winner of the 2007 Lanchester Prize, Informs


"The authors have done a wonderful job of explaining how they developed new techniques in response to the challenges posed by ever larger instances of the Traveling Salesman Problem."--MAA Online

"By bringing together the best work from a wide array of researchers, advancing the field where needed, describing their findings in a book, and implementing everything in an extremely well-written computer program, the authors show how research in computational combinatorial optimization should be done."--Michael Trick, Operations Research Letters

"The book is certainly a must for every researcher in practical TSP-computation."--Ulrich Faigle, Mathematical Reviews

"It is very well written and clearly structured. Many examples are provided, which help the reader to better understand the presented results. The authors succeed in describing the TSP problem, beginning with its history, and the first approaches, and ending with the state of the art."--Stefan Nickel, Zentralblatt MATH

"[T]the text read[s] more like a best-seller than a tome of mathematics. . . . The resulting book provides not only a map for understanding TSP computation, but should be the starting point for anyone interested in launching a computational assault on any combinatorial optimization problem."--Jan Karel Lenstra, SIAM Review

"By bringing together the best work from a wide array of researchers, advancing the field where needed, describing their findings in a book, and implementing everything in an extremely well-written computer program, the authors show how research in computational combinatorial optimization should be done."--Michael Trick, ScienceDirect

"[T]he book provides a comprehensive treatment of the traveling salesman problem and I highly recommend it not only to specialists in the area but to anyone interested in combinatorial optimization."--EMS Newsletter

From the Back Cover


"This book addresses one of the most famous and important combinatorial-optimization problems--the traveling salesman problem. It is very well written, with a vivid style that captures the reader's attention. Many examples are provided that are very useful to motivate and help the reader to better understand the results presented in the book."--Matteo Fischetti, University of Padova


"This is a fantastic book. Ever since the early days of discrete optimization, the traveling salesman problem has served as the model for computationally hard problems. The authors are main players in this area who forged a team in 1988 to push the frontiers on how good we are in solving hard and large traveling salesman problems. Now they lay out their views, experience, and findings in this book."--Bert Gerards, Centrum voor Wiskunde en Informatica



Product Details

  • File Size: 14330 KB
  • Print Length: 608 pages
  • Publisher: Princeton University Press (September 19, 2011)
  • Publication Date: September 19, 2011
  • Sold by: Amazon Digital Services LLC
  • Language: English
  • ASIN: B005Z67DK4
  • Text-to-Speech: Enabled
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  • Amazon Best Sellers Rank: #942,343 Paid in Kindle Store (See Top 100 Paid in Kindle Store)
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More About the Author

William Cook is a professor of Combinatorics and Optimization at the University of Waterloo, a member of the National Academy of Engineering, a Fellow of the American Mathematical Society, a Fellow of the Society for Industrial and Applied Mathematics (SIAM), and a Fellow of INFORMS. Together with David Applegate, Robert Bixby, and Vasek Chvatal, Cook created the Concorde computer code for the traveling salesman problem.

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Format: Hardcover
The coauthors have been working at solving large scale traveling saleman problem instances for more than 20 years. This book, along with the publicly available Concorde code, is the culmination of that twenty years of work.

The first four chapters of the book (130 pages or so) are an extremely readable description of the use and history of the traveling salesman problem. For our field, the traveling salesman problem has been an exemplar of a hard combinatorial problem, commonly used to test new ideas in problem solving. It is no coincidence that the first papers on simulated annealing, DNA computing, and other approaches for combinatorial problems describe their methods in the context of the TSP: it is the most well known of all the problems in operations research.

The authors' primary emphasis is on computation: how can optimal tours be found? The history of TSP computation is very much the history of computational combinatorial optimization. From the fundamental work of Dantzig, Fulkerson, and Johnson in solving the famous 42-city example, through Held and Karp's relaxations andLin-Kernighan's improvement heuristics, to modern-day branch-and-cut, the TSP has been at the forefront of computational methods in our field. The description of this history is outstanding, and appropriately nontechnical, suitable for reading by beginners in operations research.

The main part of the book is on the computational approaches needed to solve large TSPs. This part is well-written, though beyond a beginner level. Despite that, it has broad interest in the way it melds computational issues (like data structures and heuristic ordering) with the theory.

At the end, this book is an exemplar for how to do research in computational operations research. While not aimed at the non-specialist, it is perfectly readable by those who have gone through an introduction in optimization or operations research.
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Format: Hardcover
The latest book by Applegate, Bixby, Chvátal, and Cook provides an excellent survey of methods that kick-started the "engine of discovery in applied mathematics", known as the Travelling Salesman Problem (TSP). In more than 600 pages, the authors present a survey of methods used in their present-best TSP solver Concorde, almost to the exclusion of any other content. Chapters 1-4 describe the TSP and Chapters 5-6 provide a brief introduction to solving the TSP by using the branch and cut method. At the heart of the book are then Chapters 7-11, which survey various classes of cuts, in some cases first proposed by the authors themselves. Chapter 7 surveys cuts from blossoms and blocks, Chapter 8 presents cuts from combs and consecutive ones, and Chapter 9 introduces cuts from dominoes. Chapters 11 and 12 then describe in yet more detail separation and metamorphoses of strong valid inequalities. Other variants of the problem, such as the asymmetric TSP, and other solution approaches, including metaheuristics and approximation algorithms, are mentioned only in the passing. They are, however, well-covered elsewhere (Gutin & Punnen, 2002), and the seemingly narrow focus consequently enables the authors to provide an outstandingly in-depth treatment.

I cannot be stressed enough how much the treatment benefits from authors' extensive experience with development of Concorde ([...] In many textbooks on combinatorial optimisation, primal heuristics are mentioned only in passing and cuts are presented in the very mathematical style of definition - proof of validity - proof of dimensionality. Not here.
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Format: Hardcover Verified Purchase
This book covers almost all techniques and approaches to solve the TSP. The authors were the greater contributors to the construction of exact and heuristic solutions we know about. The salesman problem still is challenger to the students and still has a strong appeal. We can look around to other interesting problems, but sometimes we look again to TSP to check for improvements. The TSP is one of the simplest ones to enunciate but it is NP hard.
Probably it is hard also to find another book as complete like this one.
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Format: Hardcover Verified Purchase
The book is great, and unique. It goes deeply inside the exciting TSP linear programming algorithms for symmetrical problems.
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