Interfaces in Computer Science and Operations Research: Advances in Metaheuristics, Optimization, and Stochastic Modeling Technologies / Edition 1

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The disciplines of Computer Science and Operations Research have been linked since their origins and each have contributed to the dramatic advances of the other. This volume examines some of the recent advances resulting from the confluence between these two technical communities. In the process the book brings together the original work of academic researchers and practitioners in Computer Science, Operations Research, Management Science, Artificial Intelligence, Neural Networks, and related fields. More specifically, it explores the connections between these two areas with an array of advances in metaheuristics, neural networks, optimization, shastic analysis, constraint logic programming, and decision support modeling. The book's principal theme centers on the shared modeling technologies of Computer Science and Operations Research and applies these methodologies to a variety of applications in manufacturing, logistics, finance, and telecommunications.
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Editorial Reviews

Explores how high-performance computing methods have led to advances in operations research deployment, and how operations research has contributed in turn to the design and development of advanced computer systems. Describes new approaches to complex problems based on neural networks, genetic algorithms, mathematical programming, stochastic methods, constraint programming, and logical analysis. Also surveys applications of the methods to such areas as telecommunications network design, financial engineering, manufacturing, project management, forecasting, airline and machine scheduling, and vehicle routing. The 19 papers were among those presented at a conference in Dallas, Texas, in January 1996. No index. Annotation c. by Book News, Inc., Portland, Or.
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Product Details

Table of Contents

Part I: Metaheuristics. 1. Tabu Search and Adaptive Memory Programming - Advances, Applications and Challenges; F. Glover. Part II: Neural Networks. 2. Neural Networks in Practice: Survey Results; B.L. Golden, et al. 3. Tractable Theories for the Synthesis of Neural Networks; V. Chandru, et al. 4. Neural Network Training via Quadratic Programming; T.B. Trafalis, N.P. Couellan. 5. A Neural Network Model for Predicting Atlantic Hurricane Activity; O. Kwon, et al. Part III: Optimization. 6. An Efficient Dual Simplex Optimizer for Generalized Networks; J.L. Kennington, R.A. Mohammed. 7. Solving Large-Scale Crew Scheduling Problems; H.D. Chu, et al. Part IV: Constraint and Logic Programming. 8. HOURIA III: A Solver for Hierarchical Systems of Functional Constraints, Planning the Solution Graph for a Weighted Sum Criterion; M. Bouzoubaa, et al. 9. Some Recent Developments of Using Logical Analysis for Inferring a Boolean Function with a Few Clauses; E. Triantaphyllou, et al. Part V: Shastic Performance Analysis. 10. Computational Analysis of a G/G/1 Queue with Vacations and Exhaustive Service; H. Li, Y. Zhu. 11. Stability and Queuing-Time Analysis of a Reader-Writer Queue with Writer Preference; L.C. Puryear, V.G. Kulkarni. 12. Importance Sampling in Lattice Pricing Models; S.S. Nielsen. Part VI: Modeling and Decision Support. 13. Data and Optimization Modelling: A Tool for Elicitation and Browsing (DOME); H. Mousavi, et al. 14. Enhancing User Understanding via Model Analysis in a Decision Support System; D.M. Steiger. Part VII: Applications in Manufacturing, Logistics, and Finance. 15. Bank Failure Prediction Using DEA to Measure Management Quality; R.S. Barr, T.F. Siems. 16. A Cooperative Multi-Agent Approach to Constrained Project Scheduling; D. Zhu, R. Padman. 17. Scheduling a Flow Shop to Minimize the Maximal Lateness under Arbitrary Precedence Constraints; J. Józefowska, A. Zimmiak. 18. A Genetic Programming Approach for Heuristic Selection in Constrained Project Scheduling; R. Padman, S.F. Roehrig. 19. Coupling a Greedy Route Construction Heuristic with A Genetic Algorithm for the Vehicle Routing Problem with Time Windows; J.-Y. Potvin, F. Guertin.
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