# lecture 1 - Math 482(Lecture 1 Introduction Today we will...

This preview shows pages 1–2. Sign up to view the full content.

Math 482 (Lecture 1): Introduction Today: we will discuss (roughly) Section 1.1 and 2.1 of the textbook 1. What is Mathematical Optimization? * Mathematical optimization is the study of algorithms to maximize (or minimize) an objective function over a feasible region . Examples: Objective function="profit", "love match", "personal interest" (the last two are intentionally ambiguous) Examples: Feasible region defined by "resources", "available partners", "time" Key issue: How to convert ambiguity into mathematical programs ? -- Algorithms can be controversial "Real" people care: (three searches) Searched for jobs in "Mathematical optimization" and for "linear programming" and finally my own research area: "algebraic combinatorics" 2. What is Linear Programming? * Linear programming is the case of mathematical optimization where the -- objective function is defined by a linear function (in many variables); and -- the feasible region is defined by linear inequalities and equalities Wikipedia gives a good overview of the main ideas Some history. Culture of this material/course:

This preview has intentionally blurred sections. Sign up to view the full version.

View Full Document
This is the end of the preview. Sign up to access the rest of the document.

{[ snackBarMessage ]}

### Page1 / 3

lecture 1 - Math 482(Lecture 1 Introduction Today we will...

This preview shows document pages 1 - 2. Sign up to view the full document.

View Full Document
Ask a homework question - tutors are online