Class Notes
(808,147)

Canada
(493,093)

Wilfrid Laurier University
(17,900)

Business
(3,224)

BU275
(68)

David Wheatley
(20)

Lecture 1

#
BU275 Lecture 1: BU-275 Lecture 1
Premium

Unlock Document

Wilfrid Laurier University

Business

BU275

David Wheatley

winter

Description

BU-275Lecture1
Intro to Linear Programming
Motivating Example: Craft Brewery
A constrained resource problem and a revenue maximization problem
In the brewery today, we have: 50 kg of barley, 28 ounces of Hops.
It takes 5kg of barley and 2 ounces of Hops to make 20L of Lager
It takes 2kg of barley and 4 ounces of Hops to make 20L of Ale
The 20L Lager sells for $80
The 20L Ale sells for $100
How many kegs of Lager and Ale should we make today to maximize revenue?
Solution Techniques:
Linear Programming Formulation:
1. Define Decision Variables: Let x represent the number of kegs of Lager. Let y represent the
number of kegs of Ale.
2. Objective Function: Maximize 80x+100y
a. The objective function calculates an objective value (ex. Revenue)
3. Constraints: Can be built using a resource table
Lager Ale Available
Barley 5 2 50
Hops 2 4 28
Barley Constraint: 5x+2y is less than or equal to 50
Hops Constraint: 2x+4y is less than or equal to 28
Left hand side computes the amount of resources used. Right hand side computes the resources
available.
Our Linear Program:
Max revenue: 80x+100y
Subject to: 5x+2y50 and 2x+4y28
Non-negativity constraints x-y0
Solving Methods: Graphically using Corner Point Method
1. Graph the problem, by graphing the constraints as if they were lines with = signs
a. 5X+2Y=50 and 2X+4Y=28
2. Next, we identify the Feasible Region a. A feasible solution is one that satisfies all constraints
b. The feasible region is the set of all feasible solutions
c. There is at most 1 feasible region, a problem with no feasible solutions is called

More
Less
Related notes for BU275