1. Introduction -- 2. Linear Programming -- 3. Nonlinear Programming -- 4. Discrete Optimization -- 5. Optimization Under Uncertainty -- 6. Multi-objective Optimization -- 7. Optimal control and Dynamic Optimization
Summary
The author provides scientists, researchers and analysts in various fields with opportunities to identify and apply algorithms, methods and tools from the diverse areas of optimization to their own field without getting into too much detail about the underlying theories
