Catherine C. McGeoch – författare

Computational experiments on algorithms can supplement theoretical analysis by showing what algorithms, implementations and speed-up methods work best for specific machines or problems. This book guides the reader through the nuts and bolts of the major experimental questions: What should I measure? What inputs should I test? How do I analyze the data? To answer these questions the book draws on ideas from algorithm design and analysis, computer systems, and statistics and data analysis. The wide-ranging discussion includes a tutorial on system clocks and CPU timers, a survey of strategies for tuning algorithms and data structures, a cookbook of methods for generating random combinatorial inputs, and a demonstration of variance reduction techniques. The book can be used by anyone who has taken a course or two in data structures and algorithms. A companion website, AlgLab (www.cs.amherst.edu/alglab) contains downloadable files, programs and tools for use in experimental projects.

Interest has grown recently in the application of computational and statistical tools to problems in the analysis of algorithms. In many algorithmic domains worst-case bounds are too pessimistic and tractable probabilistic models too unrealistic to provide meaningful predictions of practical algorithmic performance. Experimental approaches can provide knowledge where purely analytical methods fail and can provide insights to motivate and guide deeper analytical results. The DIMACS Implementation Challenge was organized to encourage experimental work in the area of network flows and matchings. Participants at sites in the U.S., Europe, and Japan undertook projects between November 1990 and August 1991 to test and evaluate algorithms for these problems. The Challenge culminated in a three-day workshop held in October 1991 at DIMACS.This volume contains the revised and refereed versions of twenty-two of the papers presented at the workshop, along with supplemental material about the Challenge and the Workshop.

Computational experiments on algorithms can supplement theoretical analysis by showing what algorithms, implementations and speed-up methods work best for specific machines or problems. This book guides the reader through the nuts and bolts of the major experimental questions: What should I measure? What inputs should I test? How do I analyze the data? To answer these questions the book draws on ideas from algorithm design and analysis, computer systems, and statistics and data analysis. The wide-ranging discussion includes a tutorial on system clocks and CPU timers, a survey of strategies for tuning algorithms and data structures, a cookbook of methods for generating random combinatorial inputs, and a demonstration of variance reduction techniques. The book can be used by anyone who has taken a course or two in data structures and algorithms. A companion website, AlgLab (www.cs.amherst.edu/alglab) contains downloadable files, programs and tools for use in experimental projects.

Adiabatic quantum computation (AQC) is an alternative to the better-known gate model of quantum computation.Table of Contents: Acknowledgments / Introduction / Adiabatic Quantum Computation / Quantum Annealing / The D-Wave Platform / Computational Experience / Bibliography / Author's Biography

This book constitutes the thoroughly refereed post-workshop proceedings of the International Workshop on Algorithmic Engineering and Experimentation, ALENEX'99, held in Baltimore, Maryland, USA, in January 1999.The 20 revised full papers presented were carefully selected from a total of 42 submissions during two rounds of reviewing and improvement. The papers are organized in sections on combinatorial algorithms, computational geometry, software and applications, algorithms for NP-hard problems, and data structures.

The Workshop on Experimental Algorithms, WEA, is intended to be an int- national forum for research on the experimental evaluation and engineering of algorithms, as well as in various aspects of computational optimization and its applications. The emphasis of the workshop is the use of experimental me- ods to guide the design, analysis, implementation, and evaluation of algorithms, heuristics, and optimization programs. WEA 2008 was held at the Provincetown Inn, Provincetown, MA, USA, on May 30 – June 1, 2008. This was the seventh workshop of the series, after Rome (2007),Menorca(2006),Santorini(2005),RiodeJaniero(2004),Asconia(2003), and Riga (2001). This volume contains all contributed papers accepted for presentation at the workshop. The 26 contributed papers were selected by the Program Committee onthebasisofatleastthreerefereereports,somecontributedbytrustedexternal referees. In addition to the 26 contributed papers, the program contained two invited talks. Camil Demetrescu, of the University of Rome “La Sapienza,” spoke on “Visualization in Algorithm Engineering.” David S. Johnson of AT & T Labs – Research, gave a talk on “Bin Packing: From Theory to Experiment and Back Again.” We would like to thank the authors who responded to the call for papers, our invited speakers, the members of the ProgramCommittee, the external referees, and the Organizing Committee members for making this workshop possible.