index.Rmd

---
title: "Introduction to Optimization"
author: "Apurva Nakade"
date: "`r Sys.Date()`"
output: pdf_document
documentclass: book
github-repo: apurvanakade/Introduction-to-Optimization
url: https\://github.com/apurvanakade/Introduction-to-Optimization
description: Introduction to Optimization.
site: bookdown::bookdown_site
bibliography: [references.bib]
link-citations: true
nocite: '@*' 
---

```{r, setup, include=FALSE}

options(tinytex.verbose = TRUE)

knitr::opts_chunk$set(
  comment = NA, 
  echo = FALSE, 
  warning = FALSE, 
  cache=TRUE
)

```

# Preface {.unnumbered}

These are class notes for a quarter long course on *Introduction to Optimization* (Math 368) at Northwestern University taught during the Winter and Spring of 2022. The class is aimed at upper-level undergrads who've completed a basic sequence in linear algebra and calculus. The prerequisites for the linear programming part are Gaussian elimination and basic theorem proving. For the non-linear programming part, you'll need to know basic properties of gradients and directional derivatives.

The textbook used in the class was *Linear Programming, Foundations and Extensions*, by Robert J. Vanderbei. The textbook is freely available to Northwestern students via [SpringerLink](https://link.springer.com/book/10.1007/978-1-4614-7630-6). The textbook was used mainly as a reference for examples and exercises.

These notes are licensed under a [Creative Commons Attribution-ShareAlike 4.0 International License]([http://creativecommons.org/licenses/by-sa/4.0/](http://creativecommons.org/licenses/by-sa/4.0/)).
Any suggestions and improvements to the notes are welcome and greatly appreciated. 
You can [send me an email](mailto:apurva.nakade@northwestern.edu) or [open an issue](https://github.com/apurvanakade/Introduction-to-Optimization/issues) on Github. 


![](images/cc-by-sa-4.png "Creative Commons License")