|Optimization in Operations Research||
Optimization in Operations Research
|103.50||approx. 7-9 days|
For first courses in operations research, operations management.
Covers a broad range of optimization techniques, including linear programming, network flows, integer/combinational optimization, and nonlinear programming. Emphasizes the importance of modeling and problem formulation, this text teaches students how to apply algorithms to real-world problems to arrive at optimal solutions.
Visit the author-maintained web site athttp://comp.uark.edu/~rrardin/oorbook
Prepares students for the variety of model forms needed in practice and provides instructors with flexibility in depth of coverage (Chapter 2).
Allows instructors to efficiently treat both simplex and interior-point methods for linear programming (Chapter 3).
1. Problem Solving with Mathematical Models.
2. Deterministic Optimization Models in Operations Research.
3. Improving Search.
4. Linear Programming Models.
5. Simplex Search for Linear Programming.
6. Interior Point Methods for Linear Programming.
7. Duality and Sensitivity in Linear Programming.
8. Multiobjective Optimization and Goal Programming.
9. Shortest Path and Discrete Dynamic Programming.
10. Network Flows.
11. Discrete Optimization Models.
12. Discrete Optimization Methods.
13. Unconstrained Nonlinear Programming.
14. Constrained Nonlinear Programming.