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OPSM 301 Operations Management Class 10: Introduction to Linear Programming Koç University Zeynep Aksin

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Presentation on theme: "OPSM 301 Operations Management Class 10: Introduction to Linear Programming Koç University Zeynep Aksin"— Presentation transcript:

1 OPSM 301 Operations Management Class 10: Introduction to Linear Programming Koç University Zeynep Aksin

2 Announcements  Assignment 2 due on Monday  Midterm 1 next Wednesday  On Monday October 31, OPSM 301 class will be held in the computer lab SOS 180 –Graded class participation activity –Will show how to use Excel Solver to solve linear programs –You will need this for assignment 3

3 A Kristen’s like example 10 min/unit2 min/unit 6 min/unit Flow time T = = 18 min. System cycle time 1/R= 10 min. Throughput rate R= 6 units / hour Utilizations: R1: 2/10=20% R2=100% (bottleneck) R3=6/10=60% R1R2R3

4 Tools: Gantt Chart Gantt charts show the time at which different activities are performed, as well as the sequence of activities Resources time activities

5 R2 10 min/unit R1 2 min/unit R3 6 min/unit R1 R2 R Three Workers W1 W2W3

6 R1 R2 R Three Workers Throughput time for an order of 5 units System cycle time Throughput time for a rush order of 1 unit

7 R1 R2 R W1 W2 Two Workers

8 Continue Kristen’s Cookie story..  The business matures  Demand information is available  You and your roommate decide to focus on chocolate chip or oatmeal raisin cookies

9 Product Mix Decisions: Kristen Cookies offers 2 products Sale Price of Chocolate Chip Cookies:$5.00/dozen Cost of Materials:$2.50/dozen Sale Price of Oatmeal Raisin Cookies:$5.50/dozen Cost of Materials:$2.40/dozen Maximum weekly demand of Chocolate Chip Cookies:100 dozen Maximum weekly demand of Oatmeal Raisin Cookies:50 dozen Total weekly operating expense$270

10 Product Mix Decisions Total time available in week:20 hrs

11 Product Mix Decisions Margin per dozen Chocolate Chip cookies = $2.50 Margin per dozen Oatmeal Raisin cookies = $3.10 Margin per oven minute from Chocolate Chip cookies = $2.50 / 10 = $ Margin per oven minute from Oatmeal Raisin cookies = $3.10 / 15 = $ 0.207

12 Baking only one type  If I bake only chocolate chip: –In 20 hours I can bake 120 dozen –At a margin of 2.50 I will make 120*2.5=300 –But my demand is only 100 dozen!  If I bake only oatmeal raisin: –In 20 hours I can bake 80 dozen –At a margin of 3.10 I will make 80*3.10=248 –But my demand is only 50 dozen!  What about a mix of chocolate chip and oatmeal raisin? What is the best product mix?

13 Linear programming

14 Announcement  Linear programming: Appendix A from another book-copy in course pack  Skip graphical solution, skip sensitivity analysis for now  You can use examples done in class, example A1, solved problem 1, Problem 3 as a study set (and all other problems if you like)

15 Introduction  We all face decision about how to use limited resources such as: –time –money –workers/manpower

16 Mathematical Programming...  find the optimal, or most efficient, way of using limited resources to achieve objectives.  Optimization

17 Example Applications  OPSM: Product mix problem-how much of each product should be produced given resource constraints to maximize profits  Finance: Construct a portfolio of securities that maximizes return while keeping "risk" below a predetermined level  Marketing: Develop an advertising strategy to maximize exposure of potential customers while staying within a predetermined budget

18 Components of Linear Programming  A specified objective or a single goal, such as the maximization of profit, minimization of machine idle time etc.  Decision variables represent choices available to the decision maker in terms of amounts of either inputs or outputs  Constraints are limitations which restrict the alternatives available to decision makers

19 Conditions for Applicability of Linear Programming  Resources must be limited  There must be an objective function  There must be linearity in the constraints and in the objective function  Resources and products must be homogeneous  Decision variables must be divisible and non- negative

20 Components of Linear Programming  There are three types of constraints: –(=<) An upper limit on the amount of some scarce resource –(>=) A lower bound that must be achieved in the final solution –(=) An exact specification of what a decision variable should be equal to in the final solution  Parameters are fixed and given values which determine the relationships between the decision variables of the problem

21 LP for Optimal Product Mix Selection xcc:Dozens of chocolate chip cookies sold. xor:Dozens of oatmeal raisin cookies sold. Max 2.5 xcc xor subject to 8 xcc+ 5 xor< xcc +15 xor< xcc+ 4 xor<1200 xcc< 100 xor< 50 Technology Constraints Market Constraints

22 Solving the LP using Excel Solver Number to make Total profit Unit Profits ConstraintsValueRHS (constraint) You Oven Room Mate Market cc10100 Market or Constraint not binding in optimal solution Optimal Profit Optimal product-mix

23 Reading the variable information  The optimal solution for Kristen’s is to produce, 100 dozen chocolate chip and dozen oatmeal raisin resulting in an optimal profit of $ (This is the maximum possible profit attainable with the current resources)

24 Follow me using the file on the network drive  Go to STORAGE  E:\COURSES\UGRADS\OPSM301\SHARE  Copy KristensLPexample.xls to your desktop  Open the spreadsheet and click on first worksheet

25 How Solver Views the Model  Target cell - the cell in the spreadsheet that represents the objective function  Changing cells - the cells in the spreadsheet representing the decision variables  Constraint cells - the cells in the spreadsheet representing the LHS formulas on the constraints

26 Goals For Spreadsheet Design  Communication - A spreadsheet's primary business purpose is that of communicating information to managers.  Reliability - The output a spreadsheet generates should be correct and consistent.  Auditability - A manager should be able to retrace the steps followed to generate the different outputs from the model in order to understand the model and verify results.  Modifiability - A well-designed spreadsheet should be easy to change or enhance in order to meet dynamic user requirements.

27 Lets consider a slightly different version  Unit profits from Aqua-Spas is $325  Available hours of labor is 1500  Make the appropriate changes in your spreadsheet and resolve.

28 An Example LP Problem Blue Ridge Hot Tubs produces two types of hot tubs: Aqua-Spas & Hydro-Luxes. Find profit maximizing product-mix. There are 200 pumps, 1566 hours of labor, and 2880 feet of tubing available. Aqua-SpaHydro-Lux Pumps11 Labor 9 hours6 hours Tubing12 feet16 feet Unit Profit$350$300

29 5 Steps In Formulating LP Models: 1. Understand the problem 2. Identify the decision variables: X 1 =number of Aqua-Spas to produce X 2 =number of Hydro-Luxes to produce 3.State the objective function as a linear combination of the decision variables: MAX: Profit = 350X X 2

30 5 Steps In Formulating LP Models (continued) 4. State the constraints as linear combinations of the decision variables. 1X 1 + 1X 2 <= 200} pumps 9X 1 + 6X 2 <= 1566} labor 12X X 2 <= 2880} tubing 5. Identify any upper or lower bounds on the decision variables. X 1 >= 0 X 2 >= 0

31 Summary of the LP Model for Blue Ridge Hot Tubs MAX: 350X X 2 S.T.:1X 1 + 1X 2 <= 200 9X 1 + 6X 2 <= X X 2 <= 2880 X 1 >= 0 X 2 >= 0

32 Solving LP Problems: An Intuitive Approach  Idea: Each Aqua-Spa (X 1 ) generates the highest unit profit ($350), so let’s make as many of them as possible!  How many would that be? –Let X 2 = 0 1st constraint:1X 1 <= 200 2nd constraint:9X 1 <=1566 or X 1 <=174 3rd constraint:12X 1 <= 2880 or X 1 <= 240  If X 2 =0, the maximum value of X 1 is 174 and the total profit is $350*174 + $300*0 = $60,900  This solution is feasible, but is it optimal?  No!

33 The Steps in Implementing an LP Model in a Spreadsheet 1.Organize the data for the model on the spreadsheet. 2.Reserve separate cells in the spreadsheet to represent each decision variable in the model. 3.Create a formula in a cell in the spreadsheet that corresponds to the objective function. 4.For each constraint, create a formula in a separate cell in the spreadsheet that corresponds to the left-hand side (LHS) of the constraint.

34 Let’s Implement a Model for the Blue Ridge Hot Tubs Example... MAX: 350X X 2 } profit S.T.:1X 1 + 1X 2 <= 200} pumps 9X 1 + 6X 2 <= 1566} labor 12X X 2 <= 2880} tubing X 1, X 2 >= 0} nonnegativity

35 Preparing Excel  You need the Solver add-in  First check whether you have this add-in –Click on the DATA tab –Check if you have Solver under Analysis (far right)  If not –Click on the Office Button (far left top) –Click on Excel Options (bottom of dialogue box) –Select Add-Ins from menu on the left –Add Solver add-in from the right menu

36 In-class exercise  Prepare a spreadsheet for the Blue Ridge Hot Tubs product mix problem we just formulated  Solve the LP using solver  Save the file with your name_lastname in E:\COURSES\UGRADS\OPSM301\HOMEWORK  Consider the following changes –Unit profits from Aqua-Spas is $325 –Available hours of labor is 1500 –Make the appropriate changes in your spreadsheet and resolve.

37 Implementing the Model


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