The next wave in computing, optimization, and decision technologies
(eBook)
Series:
Published:
New York : Springer, ©2005., New York : Springer, [2005].
Format:
eBook
ISBN:
0387235280, 9780387235288, 0387235299, 9780387235295, 9786610189939, 6610189935
Content Description:
1 online resource (vii, 396 pages) : illustrations.
Status:
Available Online
Description
THE NEXT WAVE IN COMPUTING, OPTIMIZATION, AND DECISION TECHNOLOGIES is divided into six sections. The first section contains two papers on network models. The second section focuses in integer and mixed integer programming. The third section contains papers in which heuristic search and metaheuristics are applied. Three papers using stochastic modeling comprise the fourth section. In the fifth section, the unifying theme is software and modeling. The sixth section contains four papers on classification, clustering, and ranking. Each article in the volume has been carefully reviewed and revised accordingly. Computer Science and Operations Research continue to have a synergistic relationship and this book represents the results of the cross-fertilization between OR/MS and CS/AI. It is this interface of OR/CS that makes possible advances that could not have been achieved in isolation. Taken collectively, these articles are indicative of the state-of-the-art in the interface between OR/MS and CS/AI and of the high-caliber research being conducted by members of the INFORMS Computing Society.
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APA Citation (style guide)
Golden, B. L., Raghavan, S., & Wasil, E. A. (2005). The next wave in computing, optimization, and decision technologies. New York, Springer.
Chicago / Turabian - Author Date Citation (style guide)Golden, Bruce L., 1950-, S. Raghavan and Edward A. Wasil. 2005. The Next Wave in Computing, Optimization, and Decision Technologies. New York, Springer.
Chicago / Turabian - Humanities Citation (style guide)Golden, Bruce L., 1950-, S. Raghavan and Edward A. Wasil, The Next Wave in Computing, Optimization, and Decision Technologies. New York, Springer, 2005.
MLA Citation (style guide)Golden, Bruce L., et al. The Next Wave in Computing, Optimization, and Decision Technologies. New York, Springer, 2005.
Note! Citation formats are based on standards as of July 2022. Citations contain only title, author, edition, publisher, and year published. Citations should be used as a guideline and should be double checked for accuracy.
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Language:
English
UPC:
10.1007/b101696
Notes
Bibliography
Includes bibliographical references.
Restrictions on Access
Access is restricted to subscribing institutions.
Description
THE NEXT WAVE IN COMPUTING, OPTIMIZATION, AND DECISION TECHNOLOGIES is divided into six sections. The first section contains two papers on network models. The second section focuses in integer and mixed integer programming. The third section contains papers in which heuristic search and metaheuristics are applied. Three papers using stochastic modeling comprise the fourth section. In the fifth section, the unifying theme is software and modeling. The sixth section contains four papers on classification, clustering, and ranking. Each article in the volume has been carefully reviewed and revised accordingly. Computer Science and Operations Research continue to have a synergistic relationship and this book represents the results of the cross-fertilization between OR/MS and CS/AI. It is this interface of OR/CS that makes possible advances that could not have been achieved in isolation. Taken collectively, these articles are indicative of the state-of-the-art in the interface between OR/MS and CS/AI and of the high-caliber research being conducted by members of the INFORMS Computing Society.
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41c24664-1a68-6aa8-036f-6ce8f2b96d0f
Record Information
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| 505 | 0 | |a Cover -- Table of Contents -- Preface -- Part I Networks -- On the Complexity of Delaying an Adversary's Project -- A Note on Eswaran and Tarjan's Algorithm for the Strong Connectivity Augmentation Problem -- Part II Integer and Mixed Integer Programming -- Generating Set Partitioning Test Problems with Known Optimal Integer Solutions -- Computational Aspects of Controlled Tabular Adjustment: Algorithm and Analysis -- The SYMPHONY Callable Library for Mixed Integer Programming -- Part III Heuristic Search -- Hybrid Graph Heuristics Within a Hyper-Heuristic Approach to Exam Timetabling Problems -- Metaheuristics Comparison for the Minimum Labelling Spanning Tree Problem -- A New Tabu Search Heuristic for the Site-Dependent Vehicle Routing Problem -- A Heuristic Method to Solve the Size Assortment Problem -- Heuristic Methods for Solving Euclidean Non-Uniform Steiner Tree Problems -- Modeling and Solving a Selection and Assignment Problem -- Solving the Time Dependent Traveling Salesman Problem -- The Maximal Multiple-Representation Species Problem Solved Using Heuristic Concentration -- Part IV Stochastic Modeling -- Fast and Efficient Model-Based Clustering with the Ascent-EM Algorithm -- Statistical Learning Theory in Equity Return Forecasting -- Sample Path Derivatives for (s1 S) Inventory Systems with Price Determination -- PartV Software and Modeling -- Network and Graph Markup Language (NAGML) -- Data File Formats -- Software Quality Assurance for Mathematical Modeling Systems -- Model Development and Optimization with Mathematica -- Verification of Business Process Designs Using MAPS -- ALPS: A Framework for Implementing Parallel Tree Search Algorithms -- Part VI Classification, Clustering, and Ranking -- Tabu Search Enhanced Markov Blanket Classifier for High Dimensional Data Sets -- Dance Music Classification Using Inner Metric Analysis -- Assessing Cluster Quality Using Multiple Measures -- A Decision Tree Based Approach. | |
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