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: Stochastic 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. Jozefowska, 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.
SUMMARY OR ABSTRACT
Text of Note
The collected writings-from researchers and practitioners in Computer Science, Operations Research, Management Science, and Artificial Intelligence-were among those delivered at the Fifth INFORMS Computer Science Technical Section Conference in Dallas, Texas, January 8-10, 1996.
TOPICAL NAME USED AS SUBJECT
Artificial intelligence.
Economics.
Systems theory.
PERSONAL NAME - PRIMARY RESPONSIBILITY
edited by Richard S. Barr, Richard V. Helgason, Jeffery L. Kennington.