<p><strong>For first courses in operations research, operations management.<br/></strong>Covers a broad range of optimization techniques, including linear programming, network flows, integer/combinational optimization, and nonlinear programming. Emphasizes the importance of <strong>modeling and problem formulation</strong>, this text teaches students how to apply algorithms to real-world problems to arrive at optimal solutions.<br/> Visit the author-maintained web site at<a>http://comp.uark.edu/~rrardin/oorbook</a><br/></p>

<br/><br/><b>&nbsp;1. Problem Solving with Mathematical Models.</b> <br/><br/><br/><b>&nbsp;2. Deterministic Optimization Models in Operations Research.</b> <br/><br/><br/><b>&nbsp;3. Improving Search.</b> <br/><br/><br/><b>&nbsp;4. Linear Programming Models.</b> <br/><br/><br/><b>&nbsp;5. Simplex Search for Linear Programming.</b> <br/><br/><br/><b>&nbsp;6. Interior Point Methods for Linear Programming.</b> <br/><br/><br/><b>&nbsp;7. Duality and Sensitivity in Linear Programming.</b> <br/><br/><br/><b>&nbsp;8. Multiobjective Optimization and Goal Programming.</b> <br/><br/><br/><b>&nbsp;9. Shortest Path and Discrete Dynamic Programming.</b> <br/><br/><br/><b>10. Network Flows.</b> <br/><br/><br/><b>11. Discrete Optimization Models.</b> <br/><br/><br/><b>12. Discrete Optimization Methods.</b> <br/><br/><br/><b>13. Unconstrained Nonlinear Programming.</b> <br/><br/><br/><b>14. Constrained Nonlinear Programming.</b> <br/>

Ronald L. Rardin

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Optimization in Operations Research

Optimization in Operations Research, Pearson New International Edition

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Optimization in Operations Research, Pearson New International Edition, 1st edition

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