CO250 Study Guide - Quiz Guide: Convex Optimization, Combinatorial Optimization, Simplex Algorithm

• School: University of Waterloo
• Department: Combinatorics and Optimization
• Course: CO250
• Professor: K, G

Document Summary

Suppose that the owner of a factory wants to maximize its production for the next 30 days. There is a limit on the resources available. Resources may include raw materials, labor, machine capacities, etc. This is an example of an optimization problem. The function that we are trying to maximize is the objective function, and the conditions imposed by the available resources are the constraints of the problem. Optimization problems are classi ed according to the type of objective function and the type of constraints. The simplest models are linear programming problems where both the constraints and the objective functions are linear. Even though this may appear at a rst glance to be overly restrictive, linear programming algorithms are used very widely. Indeed, a recent survey of fortune 500 companies shows that 85% of all respondents use such algorithms in their operations. It is not hard however, to imagine applications for which fractional variable values are not desirable.