Learning Notes - Optimization

Key Notes

• Three parameters for Linear problems
• Decision variables (Number of quantities to decide)
• Objective (Minimize / Maximize profit / time)
• Constraints (Time / Resources)
• Identify these three parameters for your problem
• Leverage existing Packages

How it solves

• Decision variable multiplied by cost, subject to the constraint
• Different modeling frameworks

Fundamentals (Link)

• Convex optimization involves minimizing a convex objective function
• Linear programming is a special case of convex optimization where the objective function is linear and the constraints consist of linear equalities and inequalities
• Linear programming is a special case of convex programming, in which the objective function is a linear

Link, Link1

• Optimization is when you search for variables that attain a global maximum or minimum of some function
• Convex optimization is a subset of optimization where the functions you work with are "convex" which just means "bowl shaped". This makes the search for maxima and minima easier since you can just " walk " on the surface of the bowl in the direction with the greatest slope to get there.

Keep Thinking!!!