Operations research : an introduction
著者
書誌事項
Operations research : an introduction
Pearson, c2017
10th ed., global ed
- : [pbk.]
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注記
Includes bibliographical references and index
内容説明・目次
内容説明
For junior/senior undergraduate and first-year graduate courses in Operations Research in departments of Industrial Engineering, Business Administration, Statistics, Computer Science, and Mathematics.
Operations Research provides a broad focus on algorithmic and practical implementation of Operations Research (OR) techniques, using theory, applications, and computations to teach students OR basics. The book can be used conveniently in a survey course that encompasses all the major tools of operations research, or in two separate courses on deterministic and probabilistic decision-making.
provides a broad focus on algorithmic and practical implementation of Operations Research (OR) techniques, using theory, applications, and computations to teach students OR basics. The book can be used conveniently in a survey course that encompasses all the major tools of operations research, or in two separate courses on deterministic and probabilistic decision-making.
With the Tenth Edition, the author preserves classical algorithms by providing essential hand computational algorithms as an important part of OR history. Based on input and submissions from OR students, professors, and practitioners, the author also includes scenarios that show how classical algorithms can be beneficial in practice. These entries are included as Aha! Moments with each dealing with stories, anecdotes, and issues in OR theory, applications, computations, and teaching methodology that can advance the understanding of fundamental OR concepts.
目次
1. What Is Operations Research?
2. Modeling with Linear Programming
3. The Simplex Method and Sensitivity Analysis
4. Duality and Post-Optimal Analysis
5. Transportation Model and Its Variants
6. Network Models
7. Advanced Linear Programming
8. Goal Programming
9. Integer Linear Programming
10. Heuristic and Constraint Programming
11. Traveling Salesperson Problem (TSP)
12. Deterministic Dynamic Programming
13. Inventory Modeling (with Introduction to Supply Chains)
14. Review of Basic Probability
15. Decision Analysis and Games
16. Probabilistic Inventory Models
17. Markov Chains
18. Queuing Systems
19. Simulation Modeling
20. Classical Optimization Theory
21. Nonlinear Programming Algorithms
Appendix A: Statistical Tables
Appendix B: Partial Answers to Selected Problems
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