Skip to content

A repository with our team's SAS Optimization Challenge project in BAIM master program at Krannert School of Management, Purdue University.

Notifications You must be signed in to change notification settings

lilianchi/SAS-Optimization-Challenge

Repository files navigation

SAS-Optimization-Challenge

In-program SAS competition for BAIMer at Purdue University.

Introduction

Building T is the corporate headquarters of the XYZ Corporation. The water used in Building T comes from two sources. The first source is through The Water Co., where like other businesses in the area, the XYZ Corporations has a contract in place with The Water Co. to provide water to their Building T at a contracted price per gallon. The second source is through XYZ’s own Water Storage Tank. Precipitation is collected, treated, stored, and used to supply water to Building T, and there is a per-gallon cost associated with this process.
XYZ Corporation has hired your team of consultants to provide solutions to water allocation at Building T.

Programming language

SAS Studio

Authors (Team: Miss YSL)

  • Mua-Hua Hsu
  • Yi-Hsuan Hsu
  • Su-Tien Lee
  • Li-Ci Chuang

Objectives

  • Objective 1 - Forecasting
  1. How many total gallons of water is Building T expected to use in each of the next four weeks?
  • Objective 2 - Optimization
  1. How many gallons will XYZ buy from The Water Co. each week?
  2. How many gallons will XYZ use from their Water Storage Tank each week?
  3. What is XYZ’s projected total water cost at the end of the next four weeks?
  4. What is XYZ’s projected ending Water Storage Tank inventory at the end of each week?
  5. How much money will XYZ save by choosing the recommended contract over the alternative contract?
  6. How many more/less gallons will be in the Water Storage Tank at the end of the four-week period compared to if the alternative contract was chosen?

Methodology

  • Objective 1 - Forecasting
  1. SAS: Additive Season
  2. SAS: Additive Winter Excel
  3. SAS: Random Walk
  4. Minitab
  5. Excel
  6. Python: ARIMA
  7. Python: SARIMAX
  8. Python: Holt-Winters
  • Objective 2 - Optimization
  1. Identify model objectives and constraints
  2. Turn into mathematical formulas
  3. Set up on SAS
  4. Run the solution on SAS
  5. Alternative set
  6. Conclusion and suggestion

Presentation Video

https://www.youtube.com/watch?v=Q-tHQltJRtg

About

A repository with our team's SAS Optimization Challenge project in BAIM master program at Krannert School of Management, Purdue University.

Topics

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages