Discrete optimization: Knapsack

This lecture reviews classic combinatorial optimization problems and demonstrates how they can be modeled as mixed integer linear problems, starting with the knapsack problem. Using the example of a hiker packing a knapsack with a weight capacity, the lecture explains how to maximize utility while staying within the weight limit by defining decision variables, the objective function, and constraints. The knapsack problem is a fundamental combinatorial optimization problem applicable in various contexts, such as asset selection for investors.