Dynamic Programming: Optimal Decision Making

Explores asset selling dynamics, optimal revenue policy, acceptance thresholds, and commodity price impact.

Explores optimization methods, including unconstrained problems, linear programming, and heuristic approaches.

Explores controlled stochastic processes, focusing on analysis, behavior, and optimization, using dynamic programming to solve real-world problems.

The Marriage Problem

Explores the marriage problem, modeling the process as a controlled stochastic process with dynamic programming algorithms to find the optimal policy for accepting bachelors.

Approximation Algorithms

Covers approximation algorithms for optimization problems, LP relaxation, and randomized rounding techniques.