Author: Catherine C. McGeoch
Publisher: Cambridge University Press
ISBN: 1107001730
Category : Computers
Languages : en
Pages : 273
Book Description
This is a guidebook for those who want to use computational experiments to support their work in algorithm design and analysis. Numerous case studies and examples show how to apply these concepts. All the necessary concepts in computer architecture and data analysis are covered so that the book can be used by anyone who has taken a course or two in data structures and algorithms.
A Guide to Experimental Algorithmics
Author: Catherine C. McGeoch
Publisher: Cambridge University Press
ISBN: 1107001730
Category : Computers
Languages : en
Pages : 273
Book Description
This is a guidebook for those who want to use computational experiments to support their work in algorithm design and analysis. Numerous case studies and examples show how to apply these concepts. All the necessary concepts in computer architecture and data analysis are covered so that the book can be used by anyone who has taken a course or two in data structures and algorithms.
Publisher: Cambridge University Press
ISBN: 1107001730
Category : Computers
Languages : en
Pages : 273
Book Description
This is a guidebook for those who want to use computational experiments to support their work in algorithm design and analysis. Numerous case studies and examples show how to apply these concepts. All the necessary concepts in computer architecture and data analysis are covered so that the book can be used by anyone who has taken a course or two in data structures and algorithms.
Experimental Algorithmics
Author: Rudolf Fleischer
Publisher: Springer
ISBN: 3540363831
Category : Computers
Languages : en
Pages : 295
Book Description
Experimental algorithmics, as its name indicates, combines algorithmic work and experimentation: algorithms are not just designed, but also implemented and tested on a variety of instances. Perhaps the most important lesson in this process is that designing an algorithm is but the first step in the process of developing robust and efficient software for applications. Based on a seminar held at Dagstuhl Castle, Germany in September 2000, this state-of-the-art survey presents a coherent survey of the work done in the area so far. The 11 carefully reviewed chapters provide complete coverage of all current topics in experimental algorithmics.
Publisher: Springer
ISBN: 3540363831
Category : Computers
Languages : en
Pages : 295
Book Description
Experimental algorithmics, as its name indicates, combines algorithmic work and experimentation: algorithms are not just designed, but also implemented and tested on a variety of instances. Perhaps the most important lesson in this process is that designing an algorithm is but the first step in the process of developing robust and efficient software for applications. Based on a seminar held at Dagstuhl Castle, Germany in September 2000, this state-of-the-art survey presents a coherent survey of the work done in the area so far. The 11 carefully reviewed chapters provide complete coverage of all current topics in experimental algorithmics.
Experimental Methods for the Analysis of Optimization Algorithms
Author: Thomas Bartz-Beielstein
Publisher: Springer Science & Business Media
ISBN: 3642025382
Category : Computers
Languages : en
Pages : 469
Book Description
In operations research and computer science it is common practice to evaluate the performance of optimization algorithms on the basis of computational results, and the experimental approach should follow accepted principles that guarantee the reliability and reproducibility of results. However, computational experiments differ from those in other sciences, and the last decade has seen considerable methodological research devoted to understanding the particular features of such experiments and assessing the related statistical methods. This book consists of methodological contributions on different scenarios of experimental analysis. The first part overviews the main issues in the experimental analysis of algorithms, and discusses the experimental cycle of algorithm development; the second part treats the characterization by means of statistical distributions of algorithm performance in terms of solution quality, runtime and other measures; and the third part collects advanced methods from experimental design for configuring and tuning algorithms on a specific class of instances with the goal of using the least amount of experimentation. The contributor list includes leading scientists in algorithm design, statistical design, optimization and heuristics, and most chapters provide theoretical background and are enriched with case studies. This book is written for researchers and practitioners in operations research and computer science who wish to improve the experimental assessment of optimization algorithms and, consequently, their design.
Publisher: Springer Science & Business Media
ISBN: 3642025382
Category : Computers
Languages : en
Pages : 469
Book Description
In operations research and computer science it is common practice to evaluate the performance of optimization algorithms on the basis of computational results, and the experimental approach should follow accepted principles that guarantee the reliability and reproducibility of results. However, computational experiments differ from those in other sciences, and the last decade has seen considerable methodological research devoted to understanding the particular features of such experiments and assessing the related statistical methods. This book consists of methodological contributions on different scenarios of experimental analysis. The first part overviews the main issues in the experimental analysis of algorithms, and discusses the experimental cycle of algorithm development; the second part treats the characterization by means of statistical distributions of algorithm performance in terms of solution quality, runtime and other measures; and the third part collects advanced methods from experimental design for configuring and tuning algorithms on a specific class of instances with the goal of using the least amount of experimentation. The contributor list includes leading scientists in algorithm design, statistical design, optimization and heuristics, and most chapters provide theoretical background and are enriched with case studies. This book is written for researchers and practitioners in operations research and computer science who wish to improve the experimental assessment of optimization algorithms and, consequently, their design.
Experimental Algorithms
Author: Panos M. Pardalos
Publisher: Springer
ISBN: 364220662X
Category : Computers
Languages : en
Pages : 469
Book Description
This volume constitutes the refereed proceedings of the 10th International Symposium on Experimental Algorithms, SEA 2011, held in Kolimpari, Chania, Crete, Greece, in May 2011. The 36 revised full papers presented together with 2 invited papers were carefully reviewed and selected from 83 submissions and present current research in the area of design, analysis, and experimental evaluation and engineering of algorithms, as well as in various aspects of computational optimization and its applications.
Publisher: Springer
ISBN: 364220662X
Category : Computers
Languages : en
Pages : 469
Book Description
This volume constitutes the refereed proceedings of the 10th International Symposium on Experimental Algorithms, SEA 2011, held in Kolimpari, Chania, Crete, Greece, in May 2011. The 36 revised full papers presented together with 2 invited papers were carefully reviewed and selected from 83 submissions and present current research in the area of design, analysis, and experimental evaluation and engineering of algorithms, as well as in various aspects of computational optimization and its applications.
Experimental Algorithms
Author: Camil Demetrescu
Publisher: Springer
ISBN: 3540728457
Category : Computers
Languages : en
Pages : 458
Book Description
This book constitutes the refereed proceedings of the 6th International Workshop on Experimental and Efficient Algorithms, WEA 2007, held in Rome, Italy, in June 2007. The 30 revised full papers presented together with three invited talks cover the design, analysis, implementation, experimental evaluation, and engineering of efficient algorithms.
Publisher: Springer
ISBN: 3540728457
Category : Computers
Languages : en
Pages : 458
Book Description
This book constitutes the refereed proceedings of the 6th International Workshop on Experimental and Efficient Algorithms, WEA 2007, held in Rome, Italy, in June 2007. The 30 revised full papers presented together with three invited talks cover the design, analysis, implementation, experimental evaluation, and engineering of efficient algorithms.
Experimental Algorithms
Author: Catherine C. McGeoch
Publisher: Springer
ISBN: 3540685529
Category : Computers
Languages : en
Pages : 371
Book Description
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.
Publisher: Springer
ISBN: 3540685529
Category : Computers
Languages : en
Pages : 371
Book Description
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.
Encyclopedia of Algorithms
Author: Ming-Yang Kao
Publisher: Springer Science & Business Media
ISBN: 0387307702
Category : Computers
Languages : en
Pages : 1200
Book Description
One of Springer’s renowned Major Reference Works, this awesome achievement provides a comprehensive set of solutions to important algorithmic problems for students and researchers interested in quickly locating useful information. This first edition of the reference focuses on high-impact solutions from the most recent decade, while later editions will widen the scope of the work. All entries have been written by experts, while links to Internet sites that outline their research work are provided. The entries have all been peer-reviewed. This defining reference is published both in print and on line.
Publisher: Springer Science & Business Media
ISBN: 0387307702
Category : Computers
Languages : en
Pages : 1200
Book Description
One of Springer’s renowned Major Reference Works, this awesome achievement provides a comprehensive set of solutions to important algorithmic problems for students and researchers interested in quickly locating useful information. This first edition of the reference focuses on high-impact solutions from the most recent decade, while later editions will widen the scope of the work. All entries have been written by experts, while links to Internet sites that outline their research work are provided. The entries have all been peer-reviewed. This defining reference is published both in print and on line.
Automatic Algorithm Selection for Complex Simulation Problems
Author: Roland Ewald
Publisher: Springer Science & Business Media
ISBN: 3834881511
Category : Computers
Languages : en
Pages : 387
Book Description
To select the most suitable simulation algorithm for a given task is often difficult. This is due to intricate interactions between model features, implementation details, and runtime environment, which may strongly affect the overall performance. An automated selection of simulation algorithms supports users in setting up simulation experiments without demanding expert knowledge on simulation. Roland Ewald analyzes and discusses existing approaches to solve the algorithm selection problem in the context of simulation. He introduces a framework for automatic simulation algorithm selection and describes its integration into the open-source modelling and simulation framework James II. Its selection mechanisms are able to cope with three situations: no prior knowledge is available, the impact of problem features on simulator performance is unknown, and a relationship between problem features and algorithm performance can be established empirically. The author concludes with an experimental evaluation of the developed methods.
Publisher: Springer Science & Business Media
ISBN: 3834881511
Category : Computers
Languages : en
Pages : 387
Book Description
To select the most suitable simulation algorithm for a given task is often difficult. This is due to intricate interactions between model features, implementation details, and runtime environment, which may strongly affect the overall performance. An automated selection of simulation algorithms supports users in setting up simulation experiments without demanding expert knowledge on simulation. Roland Ewald analyzes and discusses existing approaches to solve the algorithm selection problem in the context of simulation. He introduces a framework for automatic simulation algorithm selection and describes its integration into the open-source modelling and simulation framework James II. Its selection mechanisms are able to cope with three situations: no prior knowledge is available, the impact of problem features on simulator performance is unknown, and a relationship between problem features and algorithm performance can be established empirically. The author concludes with an experimental evaluation of the developed methods.
Algorithm Engineering and Experimentation
Author: Michael T. Goodrich
Publisher: Springer
ISBN: 354048518X
Category : Computers
Languages : en
Pages : 360
Book Description
Symmetric multiprocessors (SMPs) dominate the high-end server market and are currently the primary candidate for constructing large scale multiprocessor systems. Yet, the design of e cient parallel algorithms for this platform c- rently poses several challenges. The reason for this is that the rapid progress in microprocessor speed has left main memory access as the primary limitation to SMP performance. Since memory is the bottleneck, simply increasing the n- ber of processors will not necessarily yield better performance. Indeed, memory bus limitations typically limit the size of SMPs to 16 processors. This has at least twoimplicationsfor the algorithmdesigner. First, since there are relatively few processors availableon an SMP, any parallel algorithm must be competitive with its sequential counterpart with as little as one processor in order to be r- evant. Second, for the parallel algorithm to scale with the number of processors, it must be designed with careful attention to minimizing the number and type of main memory accesses. In this paper, we present a computational model for designing e cient al- rithms for symmetric multiprocessors. We then use this model to create e cient solutions to two widely di erent types of problems - linked list pre x com- tations and generalized sorting. Both problems are memory intensive, but in die rent ways. Whereas generalized sorting algorithms typically require a large numberofmemoryaccesses, they areusuallytocontiguousmemorylocations. By contrast, prex computation algorithms typically require a more modest qu- tity of memory accesses, but they are are usually to non-contiguous memory locations.
Publisher: Springer
ISBN: 354048518X
Category : Computers
Languages : en
Pages : 360
Book Description
Symmetric multiprocessors (SMPs) dominate the high-end server market and are currently the primary candidate for constructing large scale multiprocessor systems. Yet, the design of e cient parallel algorithms for this platform c- rently poses several challenges. The reason for this is that the rapid progress in microprocessor speed has left main memory access as the primary limitation to SMP performance. Since memory is the bottleneck, simply increasing the n- ber of processors will not necessarily yield better performance. Indeed, memory bus limitations typically limit the size of SMPs to 16 processors. This has at least twoimplicationsfor the algorithmdesigner. First, since there are relatively few processors availableon an SMP, any parallel algorithm must be competitive with its sequential counterpart with as little as one processor in order to be r- evant. Second, for the parallel algorithm to scale with the number of processors, it must be designed with careful attention to minimizing the number and type of main memory accesses. In this paper, we present a computational model for designing e cient al- rithms for symmetric multiprocessors. We then use this model to create e cient solutions to two widely di erent types of problems - linked list pre x com- tations and generalized sorting. Both problems are memory intensive, but in die rent ways. Whereas generalized sorting algorithms typically require a large numberofmemoryaccesses, they areusuallytocontiguousmemorylocations. By contrast, prex computation algorithms typically require a more modest qu- tity of memory accesses, but they are are usually to non-contiguous memory locations.
Experimental Research in Evolutionary Computation
Author: Thomas Bartz-Beielstein
Publisher: Springer Science & Business Media
ISBN: 354032027X
Category : Computers
Languages : en
Pages : 221
Book Description
This book introduces the new experimentalism in evolutionary computation, providing tools to understand algorithms and programs and their interaction with optimization problems. It develops and applies statistical techniques to analyze and compare modern search heuristics such as evolutionary algorithms and particle swarm optimization. The book bridges the gap between theory and experiment by providing a self-contained experimental methodology and many examples.
Publisher: Springer Science & Business Media
ISBN: 354032027X
Category : Computers
Languages : en
Pages : 221
Book Description
This book introduces the new experimentalism in evolutionary computation, providing tools to understand algorithms and programs and their interaction with optimization problems. It develops and applies statistical techniques to analyze and compare modern search heuristics such as evolutionary algorithms and particle swarm optimization. The book bridges the gap between theory and experiment by providing a self-contained experimental methodology and many examples.