Quantitative Analysis BA 452

Similar documents
USING EXCEL SOLVER IN OPTIMIZATION PROBLEMS

INTEGRATED OPTIMIZATION OF SAFETY STOCK

SEEM 2440A/B Engineering Economics First term, Midterm Examination

Using Excel. 4. The Scenario Manager function is used to create and evaluate a collection of what-if scenarios containing multiple input values.

Sensitivity Analysis with Excel

Question 2: How will changes in the objective function s coefficients change the optimal solution?

Florida State College at Jacksonville MAC 1105: College Algebra Summer Term 2011 Reference: MW 12:00 PM 1:45 PM, South Campus Rm: G-314

Linear Programming. Solving LP Models Using MS Excel, 18

Statistics The College Board. Visit the College Board on the Web:

STUDENT EXAM PROCEDURES

Optimization Modeling for Mining Engineers

Tutorial on Using Excel Solver to Analyze Spin-Lattice Relaxation Time Data

EXPECTED LEARNING OUTCOMES:

Proximal mapping via network optimization

The University of the State of New York REGENTS HIGH SCHOOL EXAMINATION INTEGRATED ALGEBRA. Tuesday, January 22, :15 a.m. to 12:15 p.m.

Focus on minimizing costs EOQ Linear Programming. Two types of inventory costs (IC): Order/Setup Costs (OCs), and Carrying Costs (CCs) IC = OC + CC

Grade 12 Consumer Mathematics Standards Test. Written Test Student Booklet

Linear Programming Supplement E

The College Board. Visit the College Board on the Web:

Using Excel s Solver

LOS ANGELES VALLEY COLLEGE MATH 275. Ordinary Differential Equations (section # units) S16. MW 9:40 11:05a MS 108

SECTION I: Multiple Choice. It is Monday afternoon, May 2, and you will be taking the AP Psychology Exam.

Chapter 11 Monte Carlo Simulation

INTEGER PROGRAMMING. Integer Programming. Prototype example. BIP model. BIP models

A Quantitative Decision Support Framework for Optimal Railway Capacity Planning

Course Description: (Use catalog course description or approved COR)

Optimal Scheduling for Dependent Details Processing Using MS Excel Solver

Airport Planning and Design. Excel Solver

B.M.C. Durfee High School Honors Precalculus Course Syllabus

ECON Game Theory Exam 1 - Answer Key. 4) All exams must be turned in by 1:45 pm. No extensions will be granted.

1. Graphing Linear Inequalities

Frequently Asked Questions: Advanced Placement (AP) Exam

VIDEO GAME DESIGN COURSE SYLLABUS

Lecture 3. Linear Programming. 3B1B Optimization Michaelmas 2015 A. Zisserman. Extreme solutions. Simplex method. Interior point method

ALGEBRA I (Common Core) Wednesday, August 13, :30 to 11:30 a.m., only

Chapter 5. Linear Inequalities and Linear Programming. Linear Programming in Two Dimensions: A Geometric Approach

STT315 Chapter 4 Random Variables & Probability Distributions KM. Chapter 4.5, 6, 8 Probability Distributions for Continuous Random Variables

Chapter 13: Binary and Mixed-Integer Programming

II. Office Hours* (sign up at least 24 hours in advance in binder at student desk in office) Monday

Access Code: RVAE4-EGKVN Financial Aid Code: 6A9DB-DEE3B-74F

ALGEBRA I (Common Core)

High School of Business Level II Principles of Marketing Instructor: Coach Stough

Constrained Optimization: The Method of Lagrange Multipliers:

The University of the State of New York REGENTS HIGH SCHOOL EXAMINATION INTEGRATED ALGEBRA. Tuesday, January 22, :15 a.m. SAMPLE RESPONSE SET

Excel Modeling Practice. The Svelte Glove Problem Step-by-Step With Instructions

ALGEBRA I (Common Core) Thursday, June 16, :15 a.m. to 12:15 p.m., only

constraint. Let us penalize ourselves for making the constraint too big. We end up with a

Math 3E - Linear Algebra (3 units)

ISA HELP BOOKLET AQA SCIENCE NAME: Class:

Los Angeles Pierce College. SYLLABUS Math 227: Elementary Statistics. Fall 2011 T Th 4:45 6:50 pm Section #3307 Room: MATH 1400

Chapter 3 RANDOM VARIATE GENERATION

MAT 151 College Algebra and MAT 182 Trigonometry Course Syllabus Spring 2014

BAKERSFIELD COLLEGE. Elementary Probability and Statistics. Math B22 CRN SPRING 2016

Question 2: How do you solve a linear programming problem with a graph?

Student Guide and Syllabus for MAT100 Introductory Algebra

Analyzing Mission Critical Voice over IP Networks. Michael Todd Gardner

ALGEBRA I (Common Core) Monday, January 26, :15 to 4:15 p.m., only

How To Pass Onliner College Algebra 1314 Online Online Online Online Online

Math 131 College Algebra Fall 2015

CASPER COLLEGE COURSE SYLLABUS

INSTRUCTOR INFORMATION Instructor: Adrienne Petersen Office: DMS 233 Office Hours: TuTh 11am-1pm by appointment

MATHEMATICAL TOOLS FOR ECONOMICS ECON FALL 2011

Tutorial: Using Excel for Linear Optimization Problems

RANGER COLLEGE SYLLABUS

INDUSTRIAL-ORGANIZATIONAL PSYCHOLOGY

PROCURING & GETTING THE MOST FROM YOUR EVENT PLANNING INTERN

UNIVERSITY OF SOUTHERN CALIFORNIA Marshall School of Business IOM 427 Designing Spreadsheet-Based Business Models Fall 2011

5 INTEGER LINEAR PROGRAMMING (ILP) E. Amaldi Fondamenti di R.O. Politecnico di Milano 1

ALGEBRA 2/TRIGONOMETRY

MATH 245 COLLEGE ALGEBRA Section :55 1:30

Chapter 10: Network Flow Programming

The Method of Least Squares. Lectures INF2320 p. 1/80

PBJ 101 INTRODUCTION TO CRIMINAL JUSTICE

Optimization with Big Data: Network Flows

Building a Smooth Yield Curve. University of Chicago. Jeff Greco

YOU CAN COUNT ON NUMBER LINES

Module1. x y 800.

Using EXCEL Solver October, 2000

Linear Programming Notes V Problem Transformations

Simulation-based Optimization Approach to Clinical Trial Supply Chain Management

Microeconomics Sept. 16, 2010 NOTES ON CALCULUS AND UTILITY FUNCTIONS

MATH 1111 College Algebra Fall Semester 2014 Course Syllabus. Course Details: TR 3:30 4:45 pm Math 1111-I4 CRN 963 IC #322

SYLLABUS Honors College Algebra MAC 1105H / 3 credit hours Fall 2014

Math 120 Final Exam Practice Problems, Form: A

Thursday, November 13: 6.1 Discrete Random Variables

Integer Programming Formulation

COURSE SYLLABUS. Office Hours: MWF 08:30am-09:55am or by appointment, DAV 238

ISyE 2030 Test 2 Solutions

Del Mar College - Mathematics Department SYLLABUS for the Online College Algebra Math 1314 Summer 2014

Engineering Problem Solving and Excel. EGN 1006 Introduction to Engineering

Phone: (773) Spring Office hours: MW 7:30-8:20 and 11:00-12:20, T 7:30-7:50 and 9:55-12:15

TRINITY VALLEY COMMUNITY COLLEGE COURSE SYLLABUS

Economic Ordering Quantities: A Practical Cost Reduction Strategy for Inventory Management

Syllabus MAT0018 Developmental Mathematics I

Machining Operations- Cycle Time

Images of Microsoft Excel dialog boxes Microsoft. All rights reserved. This content is excluded from our Creative Commons license.

MATH 110: College Algebra

PART A: For each worker, determine that worker's marginal product of labor.

Entrepreneurship. Course Syllabus Random Lake High School. Teacher(s): Steve Wills Prerequisites: None. Grade Level(s) Duration: Semester

Notes on Continuous Random Variables

Transcription:

This is your. is a 100-minute exam (1hr. 40 min.). There are 4 questions (25 minutes per question). To avoid the temptation to cheat, you must abide by these rules then sign below after you understand the rules and agree to them: Turn off your cell phones. You cannot leave the room during the exam, not even to use the restroom. The only things you can have in your possession are pens or pencils and a simple non-graphing, non-programmable, non-text calculator. All other possessions (including phones, computers, or papers) are prohibited and must be placed in the designated corner of the room. Possession of any prohibited item (including phones, computers, or papers) during the exam (even if you don t use them but keep them in your pocket) earns you a zero on this exam, and you will be reported to the Academic Integrity Committee for further action. Print name here: Sign name here: Each individual question on the following exam is graded on a 4-point scale. After all individual questions are graded, I sum the individual scores, and then compute that total as a percentage of the total of all points possible. I then apply a standard grading scale to determine your letter grade: 90-100% A; 80-89% B; 70-79% C; 60-70% D; 0-59% F Finally, curving points may be added to letter grades for the entire class (at my discretion), and the resulting curved letter grade will be recorded on a standard 4-point numerical scale. Tip: Explain your answers. And pace yourself. When there is only ½ hour left, spend at least 5 minutes outlining an answer to each remaining question. 1

There are no computer questions on this exam. On each question, you may only use blank or graph paper, pencils, a ruler, and a calculator. You may not use a computer or notes. 2

Rounding Off Question 1. Jacuzzi produces two types of hot tubs: Fuzion and Torino. There are 5 pumps, 36 hours of labor, and 60 feet of tubing available to make the tubs per week. Here are the input requirements, and unit profits: Fuzion Torino Pumps 1 1 Labor 9 hours 4 hours Tubing 8 feet 15 feet Unit Profit $6 $9 a. Develop a linear programming model for this problem to determine how much should be produced. b. Graphically solve the linear-programming problem from Part a if you require that production units be integers. c. Graphically solve the linear-programming problem from Part a if you do not require that production units be integers (instead, production units are continuous variables). d. Compare your solutions in Parts b and c. Tip: Your written answer should define the decision variables, formulate the objective and constraints, and solve for the optimum. --- You will not earn full credit if you just solve for the optimum; you must also define the decision variables, and formulate the objective and constraints. 3

Part a: Let F = Fuzion units produced per week. Let Y = Torino units produced per week. Part c: Max 6 F + 9 T s.t. F + T < 5 (pumps) 9 F + 4 T < 36 (labor hours) 8 F + 15 T < 60 (tubing) F, T 0 10 9 8 7 6 5 4 3 2 1 0 0 1 2 3 4 5 6 7 8 9 10 A graph of the feasible set and isovalue lines (dashed lines above) reveals the optimum occurs where the first and the third constraint bind. Solving the binding form of those two constraints yields the optimal solution: F = 2.143, T = 2.857 4

Part b: Max 6 F + 9 T s.t. F + T < 5 (pumps) 9 F + 4 T < 36 (labor hours) 8 F + 15 T < 60 (tubing) F, T 0 Part c: 10 9 8 7 6 5 4 3 2 1 0 0 1 2 3 4 5 6 7 8 9 10 A graph of the feasible set dots and isovalue lines (dashed lines above) reveals the optimum occurs at either (0,4) or (1,3) or (3,2). It turns out there are two optima: (0,4) and (3,2). Part d: The integer solutions in Part b are not the result of rounding off the continuous solution in Part c. 5

Transshipment Problems with New Nodes Question 2. Apple supplies distribution centers in California, Colorado, Florida, and New York with smart phones. Apple orders computers from manufacturers in Arizona and China. Each day s demand for phones are 400 for California, 200 for Colorado, 300 for Florida, and 500 for New York. Arizona can supply up to 800 computers and China can supply up to 1200 computers. Apple can ship from Chicago, or from Las Vegas, or from Newark (or from any combination). If any units are shipped from Chicago, there is a fixed cost of 100 per day. If any units are shipped from Las Vegas, there is a fixed cost of 70 per day. If any units are shipped from Newark, there is a fixed cost of 80 per day. Unit costs from the manufacturers to the shipment centers are: Chicago Las Vegas Newark Arizona 2 5 4 China 9 8 6 The unit costs to distribution centers are: California Colorado Florida New York Chicago 3 4 6 5 Las Vegas 5 6 4 7 Newark 2 5 8 3 Formulate the linear program that minimizes the cost of meeting all demands at minimum cost. Tip: Your written answer should define the decision variables, and formulate the objective and constraints. 6

List origin, transshipment, and destination nodes in this transshipment problem: 1 = Arizona, 2 = China 3 = Chicago, 4 = Las Vegas, 5 = Newark, 6 = California, 7 = Colorado, 8 = Florida, 9 = New York. Define binary variables for transshipment nodes, Y3 = 1 if the Chicago facility is used; 0, if not Y4 = 1 if the Las Vegas facility is used; 0, if not Y5 = 1 if the Newark facility is used; 0, if not Define integer shipment variables just as in any transshipment problem, Xij = the units shipped from node i (i = 1, 2, 3, 4, 5) to node j (j = 3, 4, 5, 6, 7) on a particular day. The objective is minimize total cost. From cost data, shipping costs are 2X13 + 5X14 + 4X15 + 9X23 + 8X24 + 6X25 + 3X36 + 4X37 + 6X38 + 5X39 + 5X46 + 6X47 + 4X48 + 7X49 + 2X56 + 5X57 + 8X58 + 3X59 + From cost data, facility use fixed costs are 100Y3 + 70Y4 + 80Y5 7

Hence, the objective to minimize total costs is Min 2X13 + 5X14 + 4X15 + 9X23 + 8X24 + 6X25 + 3X36 + 4X37 + 6X38 + 5X39 + 5X46 + 6X47 + 4X48 + 7X49 + 2X56 + 5X57 + 8X58 + 3X59 + 100Y3 + 70Y4 + 80Y5 From capacity data, Arizona capacity constraint is X13 + X14+ X15 < 800 China capacity constraint is X23 + X24+ X25 < 1200 From demand data, California demand constraint is X36 + X46 + X56 > 400 Colorado demand constraint is X37 + X47+ X47 > 200 Florida demand constraint is X38 + X48 + X58 > 300 New York demand constraint is X39 + X49+ X49 > 500 Transshipment constraints are X36 + X37 + X38 + X39 < X13 + X23, through Chicago X46 + X47 + X48 + X49 < X14 + X24, through Las Vegas X56 + X57 + X58 + X59 < X15 + X25, through Newark And fixed-cost indicator constraints are X36 + X37 + X38 + X39 < 2000 Y3, through Chicago X46 + X47 + X48 + X49 < 2000 Y4, through Las Vegas X56 + X57 + X58 + X59 < 2000 Y5, through Newark 8

Capital Budgeting Question 3. Frys Electronics is planning to expand its sales operation by offering new electronic appliances. The company has identified seven new product lines it can carry. Product Line Investment Floor Space Expected Return (Percent) ($) (Square Feet) Projection TVs 6,000 125 16 Cell Phones 12,000 150 9 Plasma TVs 20,000 200 11 IPODs 14,000 40 10 DVD Players 15,000 40 8 PDAs 2,000 20 14 Computers 32,000 100 13 Frys will not stock Projection TVs unless they stock both Plasma TVs and IPODs. They will not stock both Cell Phones and PDAs. And they will stock DVD Players only if they stock Computers. Finally, the company wishes to introduce at most four new product lines. If the company has $45,000 to invest and 420 square feet of floor space available, formulate an integer linear program for Frys to maximize its overall expected return. But you need not compute an optimum. Tip: Your written answer should define the decision variables, and formulate the objective and constraints. 9

Define the Decision Variables: x 1 = 1 if product line 1 is introduced, and = 0 otherwise. And so on. Product line 1. Projection TVs Product line 2. Cell Phones Product line 3. Plasma TVs Product line 4. IPODs Product line 5. DVD Players Product line 6. PDAs Product line 7. Computers Define the Objective: Maximize total expected return. Max.16(6000)x 1 +.09(12000)x 2 +.11(20000)x 3 +.10(14000)x 4 +.08(15000)x 5 +.141(2000)x 6 +.132(32000)x 7 1. Constrain total investment by $45,000: 6000x 1 + 12000x 2 + 20000x 3 + 14000x 4 + 15000x 5 + 2000x 6 + 32000x 7 < 45,000 2. Constrain space by 420 square feet: 125x 1 +150x 2 +200x 3 +40x 4 + 40x 5 + 20x 6 + 100x 7 < 420 3. Frys will not stock Projection TVs unless they stock both Plasma TVs and IPODs: x 3 > x 1 and x 4 > x 1. Another linear way to write that constraint is x 3 + x 4 > 2x 1, and a nonlinear way is x 3 x 4 > x 1. 4. Frys will not stock both Cell Phones and PDAs: x 2 + x 6 < 1 5. Frys will stock DVD Players only if they stock Computers: x 5 < x 7 6. Frys will introduce at most four new product lines: x 1 + x 2 + x 3 + x 4 + x 5 + x 6 + x 7 < 4 10

Economic Analysis with Teamwork Question 4. Food on Foot is a 501(c)(3) nonprofit organization dedicated to providing the poor and homeless of Los Angeles with nutritious meals, clothing, and assistance in the transition to employment and life off the streets. Food on Foot operates a weekly meal program every Sunday in Hollywood. They are considering three alternative distribution systems. Arrivals to the distribution stand follow the Poisson distribution with an average of one homeless person arriving every 6 minutes. The cost for a homeless person waiting is $3 per hour. The first system involves one volunteer (who talks to the homeless and serves food and serves drinks) and costs $1 per hour to operate (the opportunity cost of the volunteer s time), and it has an exponential service rate, and it can serve an average of one homeless person every 3 minutes. The second system involves two volunteers working as a team (one talks to the homeless and serves food, and the other serves drinks) and costs $2 per hour to operate (the opportunity cost of the 2 volunteer s time), and it has an exponential service rate, and it can serve an average of one homeless person every 2 minutes. The third system involves three volunteers working as a team (one talks to the homeless, one serves food, and the third serves drinks) and costs $3 per hour to operate (the opportunity cost of the 3 volunteer s time), and it has an exponential service rate, and it can serve an average of one homeless person every 1.5 minutes. Which system should be chosen? You may use any or all of the following analytical formulas for an M/M/1 system to compute your answer: The probability of no units in the system: P 0 = 1- The average number of units in the waiting line: L q = 11

The average number of units in the system: L = L q + The average time a unit spends in the waiting line: W q = L q / The average time a unit spends in the system: W = 1/ The probability that an arriving unit has to wait: P w = Probability of n units in the system: P n = ( ) n P 0 12

First system: k = 1 channel, = 10 per hour, and = 20 per hour. The average number of units in the waiting line: L q = = 10*10/(20(10)) = 1/2 The average number of units in the system: L = L q + = 1/2 + 1/2 = 1 Cost to operate = $1 + $3*L = $4 per hour. Second system: k = 1 channel, = 10 per hour, and = 30 per hour. The average number of units in the waiting line: L q = = 10*10/(30(20)) = 1/6 The average number of units in the system: L = L q + = 1/6 + 1/3 = 1/2 = 0.50 Cost to operate = $2 + $3*L = $3.50 per hour. Third system: k = 1 channel, = 10 per hour, and = 40 per hour. The average number of units in the waiting line: L q = = 10*10/(40(30)) = 1/12 The average number of units in the system: L = L q + = 1/12 + 1/4 = 1/3 = 0.33 Cost to operate = $3 + $3*L = $4 per hour. Choose the second system. (Going beyond the basic answer, ask any other volunteers beyond two to put in extra time at work and donate their income. The homeless people will benefit more from the extra money than from the faster service.) 13