# Mat 540 Assignment

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MAT540 Student Version 1122 (11-29-2011) Final Page 1 of 19 COURSE OUTCOMES Upon the successful completion of this course, the student will be able to: 1. Describe the role of quantitative methods in business decision making. 2. Analyze decision-making problems electronically. 3. Create statistical analysis of simulation results. 4. Apply the most appropriate forecasting method for the properties of the available data. . 5. Solve linear programming problems. 6. Create sensitivity analysis on linear programming model parameters. 7.

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Apply linear programming models to project management applications. 8. Solve integer-programming problems. 9. Develop solutions for transshipment problems. 10. Use technology and information resources to research issues in Management Science 11. Communicate issues in Management Science. COURSE EXPECTATIONS To obtain the most benefit from this class: ? Follow Strayer University’s policies and procedures as well as those specific to this class. o Class specific information can be found within the “Class Information” section within the Student Center.

WEEKLY COURSE SCHEDULE The weekly schedule below describes the learning activities that will help you achieve the course outcomes listed above and the assignments that will be used to measure your mastery of the outcomes. Each week is divided into sections consisting of readings, lectures, activities and assignments. For selected assignments, you will find a rubric that will be used to evaluate your performance. Each week is divided into sections consisting of activities including readings, lectures and discussions, quizzes, and assignments. WEEK 1 Course outcome in focus: ?

Describe the role of quantitative methods in business decision making. ? Use technology and information resources to research and communicate issues in Management Science. Supporting topics: ? Management science approach to problem solving MAT540 Student Version 1122 (11-29-2011) Final Page 2 of 19 ? ? ? ? ? ? ? ? ? ? Model building: break-even analysis Computer solution Management science modeling techniques Business usage of management science techniques Management science models in decision support systems Types of probability Fundamentals of probability Statistical independence and dependence Expected value The normal distribution

Weekly Activities: Reading: ? Chapter 1, Management Science ? Chapter 11, Probability and Statistics ? Review Syllabus Parts I & II Assignments: ? Complete Week 1 Quiz Course Lectures: ? ? ? ? Lecture/discussion on faculty introduction, course overview ,and expectations Activity – Student introductions Lecture/discussion on: Overview of Management science; statistics and probability e-Activity – Probability in your profession ? Do you use probability in your profession? More than likely you do. For example, in the heath field you could say that 1 in 4 women give birth by c-section (Parenting, May 2005).

This means that the probability of giving birth by c-section is 1/4 = 0. 25 = 25%. Similar probabilities could be found in other professions. Using your favorite search engine, find an example of probability being used in your chosen profession. Explain the example and be sure to cite the source of the information clearly. Assignment: Quiz 1 Please take the quiz in the course shell for Week 1 that covers the material in Chapters 1 and 11. This is an open book, timed quiz that can only be taken once with a time limit of MAT540 Student Version 1122 (11-29-2011) Final Page 3 of 19 one hour.

The quiz consists of a combination of true/false, multiple choice, and problem questions for a total of twenty questions, ten from each chapter. Each question is worth 2 points. WEEK 2 Course outcome in focus: ? Analyze decision-making problems electronically. Supporting topics: ? Components of decision making ? Decision making without probabilities ? Decision making with probabilities ? Decision analysis with additional information Weekly Activities: Reading: ? Chapter 12, Decision Analysis Assignments: ? Complete Week 2 Quiz Course Lectures: ? ? Lecture/discussion on components of decision making through decision trees.

Activity – Decision Tree o Explain the parts of a decision tree. o What are some benefits of using decision trees? o In what ways can decision trees be used for business decisions? Name some real-world examples. Lecture/discussion on decision making without probabilities; decision making with probabilities. Activity – Probability and Decisions o How does the science of probability affect decisions? Why? ? ? Assignment: Quiz 2 Please take the quiz in the course shell for Week 2 that covers the material in Chapters 11 and 12. This is an open book, timed quiz that can only be taken once with a time limit of one hour.

The quiz consists of a combination of true/false, multiple choice, and problem questions for a total of twenty questions. Each question is worth 2 points. MAT540 Student Version 1122 (11-29-2011) Final Page 4 of 19 WEEK 3 Course outcome in focus: ? Create statistical analysis of simulation results. ? Use technology and information resources to research issues in Management Science. Supporting topics: ? The Monte Carlo process ? Computer simulation with excel spreadsheets ? Simulation of a queuing system ? Continuous probability distributions ? Statistical analysis of simulation results ? Verification of the simulation model ?

Areas of simulation application Weekly Activities: Reading: ? Chapter 14, Simulation ? Assignments: ? Complete Week 3 Case Assignment Course Lectures: ? ? Lecture/discussion on The Monte Carlo process; computer simulation with excel spreadsheets Activity – Pseudorandom numbers o Why do we use pseudorandom numbers in simulations? o How do pseudorandom numbers affect the accuracy of a simulation? Lecture/discussion on statistical analysis of simulation results; verification of the simulation model Activity – Simulation o Question for discussion: What is the role of statistical analysis in simulation? ? Assignment: Assignment #1: JET Copies Case Problem Read the “JET Copies” Case Problem on pages 678-679 of the text. Using simulation estimate the loss of revenue due to copier breakdown for one year, as follows: 1. In Excel, use a suitable method for generating the number of days needed to repair the copier, when it is out of service, according to the discrete distribution shown. 2. In Excel, use a suitable method for simulating the interval between successive MAT540 Student Version 1122 (11-29-2011) Final Page 5 of 19 3. 4. 5. 6. breakdowns, according to the continuous distribution shown.

In Excel, use a suitable method for simulating the lost revenue for each day the copier is out of service. Put all of this together to simulate the lost revenue due to copier breakdowns over 1 year to answer the question asked in the case study. In a word processing program, write a brief description/explanation of how you implemented each component of the model. Write 1-2 paragraphs for each component of the model (days-to-repair; interval between breakdowns; lost revenue; putting it together). Answer the question posed in the case study.

How confident are you that this answer is a good one? What are the limits of the study? Write at least one paragraph. There are two deliverables for this Case Problem, the Excel spreadsheet and the written description/explanation. Please submit both of them electronically via the dropbox. The assignment will be graded using the associated rubric. Outcome Assessed: Create statistical analysis of simulation results. Communicate issues in management science Grading Rubric for JET Copies Case Problem There are 12 possible points in each of the five criteria for a total of 60 points possible. Unacceptable (0 points) Did not submit or did not model this component in an appropriate manner 1 Developing (6 points) This component was modeled, but the method and/or implementation had mistakes that affected the validity of the model This component was modeled, but the method and/or implementation had mistakes that affected the validity of the model This component was modeled, but the method and/or implementation had mistakes that affected the validity of the model Provided partially developed written description that matches the method 70 – 79% accuracy. Competent (9 points) Used a method that is recognizably appropriate, but the implementation had minor mistakes 3 Exemplary (12 points) Used an appropriate method and correctly implemented it ? ? Criteria 1. Model number of days to repair 2. Model number of weeks between breakdowns Did not submit or did not model this component in an appropriate manner Used a method that is recognizably appropriate, but the implementation had minor mistakes Used an appropriate method and correctly implemented it 3. Model lost revenue due to breakdowns Did not submit or did not model this component in an appropriate manner

Used a method that is recognizably appropriate, but the implementation had minor mistakes Used an appropriate method and correctly implemented it 4. Provide written description and explanation of the simulation Did not submit or described insufficiently. Omitted key points. Provided sufficiently developed written description that matches the method 80 – 89% accuracy. Provided sufficiently correct 5. Combine model components to Did not submit or result not provided, Provided partially correct result. Provided fully developed written description that is correct and matches the method used with 90 – 100% accuracy. Provided fully correct result.

MAT540 Student Version 1122 (11-29-2011) Final Page 6 of 19 Criteria produce a coherent answer to the question posed in the case study. (a) Answer the question posed in the case study. (b) How confident are you that this answer is a good one? (c) What are the limits of the study? 0 Unacceptable (0 points) and/or discussed insufficiently. 1 Developing (6 points) Omitted discussion of confidence. Discussed limitations partially with 70 – 79% accuracy, logic, and clarity. 2 Competent (9 points) result. Identified confidence and discussed limitations sufficiently with 80 – 89% accuracy, accuracy, logic, and clarity. Exemplary (12 points) Identified confidence and discussed limitations fully with 90 – 100% accuracy, logic, and clarity. WEEK 4 Course outcome in focus: ? Apply the most appropriate forecasting method for the properties of the available data ? Use technology and information resources to research and communicate issues in Management Science. Supporting topics: ? Forecasting components ? Time series methods ? Forecast accuracy ? Time series forecasting ? Regression methods Weekly Activities: Reading: Chapter 15, Forecasting Assignments: ? Complete Internet Field Trip Course Lectures: ?

Lecture/discussion on Forecasting components; time series methods There are many ways to forecast the future. In numerous firms (especially smaller ones), the entire process is subjective, involving intuition, and years of experience. There are also many quantitative forecasting models, such as moving averages, exponential smoothing, trend projections, and least squares regression analysis. Regardless of the method that is used to make the forecast, the same eight overall procedures that follow are used. Eight Steps to Forecasting MAT540 Student Version 1122 (11-29-2011) Final Page 7 of 19 . Determine the use of the forecast what objective are we trying to obtain? 2. Select the items or quantities that are to be forecasted. 3. Determine the time horizon of the forecast is it 1 to 30 days (short term), 1 month to 1 year (medium term), or more than 1 year (long term)? 4. Select the forecasting model or models. 5. Gather the data needed to make the forecast. 6. Validate the forecasting model. 7. Make the forecast. 8. Implement the results. These steps present a systematic way of initiating, designing, and implementing a fore-casting system.

When the forecasting system is to be used to generate forecasts regularly over time, data must be collected routinely, and the actual computations or procedures used to make the forecast can be done automatically. When a computer system is used, computer forecasting files and programs are needed. There is seldom a single superior forecasting method. One organization may find regression effective, another firm may use several approaches, and a third may combine both quantitative and subjective techniques. Whatever tool works best for a firm is the one that should be used. Activity – Rationale of Forecasting o o ? ? Choose one of the forecasting methods and explain the rationale behind using it in real-life. Describe how a domestic fast food chain with plans for expanding into China would be able to use a forecasting model. Lecture/discussion on Forecast accuracy; time series forecasting; regression methods Activity – Forecasting Methods Question for discussion: o What is the difference between a causal model and a time- series model? Give an example of when each would be used. o What are some of the problems and drawbacks of the moving average forecasting model? How do you determine how many observations to average in a moving average model? How do you determine the weightings to use in a weighted moving average model? Assignment: Assignment #2: Internet Field Trip 1. Research: Research at least six (6) information sources on forecasting methods; take MAT540 Student Version 1122 (11-29-2011) Final Page 8 of 19 2. 3. 4. 5. 6. 7. notes and record and interpret significant facts, meaningful graphics, accurate sounds and evaluated alternative points of view. Preparation: Produce as storyboard with thumbnails of at least ten (10) slides.

Text Elements: (1) fonts are easy-toread; (2) point size that varies appropriately for headings, and text (3) italics, bold, and indentations enhance readability, (4) background and colors enhance the readability of text, (5) appropriate in length for the target audience; (6) to the point (7) Applied correct spelling, punctuation, grammar, and (8) APA style. 4. Layout: The layout 0 Unacceptable (0 points) from two (2) or fewer information sources. Insufficiently recorded and interpreted facts, graphics, sounds, or did not evaluate alternate points of view. Did not submit or produced insufficiently developed storyboard with thumbnails of one (1) to five (5) slides with one (1) to Two (2) required elements. Fulfilled with less than 70% accuracy, quality, and thoroughness. Developing (4 points) sources; recorded and interpreted some acceptable facts, some appropriate graphics, sounds and sufficiently evaluated alternative points of view. Produced partially developed storyboard with thumbnails of at least six (6) or seven (7) slides with three (3) of the (5) required elements. Fulfilled with 70 – 79% accuracy, quality, and thoroughness. 2 Competent (6 points) information sources; recorded and interpreted acceptable facts, appropriate graphics, accurate sounds, and sufficiently evaluated alternative points of view. Produced sufficiently developed storyboard with thumbnails of at least eight (8) slides with four (4) of the (5) required elements. Fulfilled with 80 – 89% accuracy, quality, and thoroughness. Exemplary (8 points) sources; recorded and interpreted significant facts, meaningful graphics, accurate sounds, and fully evaluated alternative points of view. Prepared fully developed storyboard with thumbnails of at least 10 slides with all five (5) required elements. Fulfilled with 90 – 100% accuracy, quality, and thoroughness. Did not submit or provided insufficiently developed introduction and content with two (2) or fewer of required elements included. Addressed with less than 70% accuracy, motivation, logic, support, and research. Provided partially developed introduction and content with three (5) of five (5) required elements included. Addressed with 7079% accuracy, motivation, logic, support, and research.

Provided sufficiently developed introduction and content with four (4) of five (5) required elements included. Addressed with 8089% accuracy, motivation, logic, support, and research. Provided excellent and fully developed introduction and content with all five (5) required elements included. Addressed with 90-100% accuracy, motivation, logic, support, and research. Did not submit or did not demonstrate acceptable use of the text elements. Issues with text elements prevented effective communication of message. Had 8 + errors in spelling, punctuation, grammar, and APA style. Demonstrated acceptable use of 4 – 5 text elements. Text elements provided some helpful support to the communication of the message.

Had 6 – 7 errors in spelling, punctuation, grammar, and APA style. Fulfilled with 70 – 79% quality and accuracy. Demonstrated sufficient use of 6 – 7 of the text elements. Text elements provided sufficient support to the communication of the message. Had no 3 – 5 errors in spelling, punctuation, grammar, and APA style. Fulfilled with 80 – 89% quality and accuracy. Demonstrated excellent use of all 8 text elements. Text elements provided outstanding support to the communication of the message. Had 0 2 errors in spelling, punctuation, grammar, and APA style. Fulfilled with 90 – 100% quality and accuracy. Did not submit or the The layout of the The layout of the The layout of the

MAT540 Student Version 1122 (11-29-2011) Final Page 10 of 19 Criteria of the message demonstrated these characteristics: (1) visually pleasing;(2) contributed to the overall message; had (3) appropriate headings, (4) subheadings, (5) and white space 0 Unacceptable (0 points) layout of the message was not acceptable and did not support communication of the message sufficiently. Layout did not include enough of the five (5) of the layout characteristics. 1 Developing (4 points) message was acceptable and supported communication of it to some extent. Layout included three (3) of the five (5) of the layout characteristics. Fulfilled with 70 – 79% quality and accuracy.

Provided media that were acceptable and met only one (1) of the three (3) characteristics. Fulfilled with 70 – 79% quality and accuracy. 2 Competent (6 points) message was good and supported communication of it sufficiently. Layout included four (4) of the five (5) of the layout characteristics. Fulfilled with 80 – 89% quality and accuracy. 3 Exemplary (8 points) message was excellent and supported communication of it very well. Layout included all five (5) of the layout characteristics. Fulfilled with 90 – 100% quality and accuracy. Provided media that were excellent and met all three (3) of the characteristics. Fulfilled with 90 – 100% quality and accuracy. 5.

Media: The media should include these characteristics: (1) graphics, sound, and/or animation that assist in presenting an overall theme and enhance understanding of concept, ideas and relationships; (2) have original images; graphics are created using proper size and resolution; enhance the content; (3) have a consistent visual theme. Did not submit or the media used were unacceptable and did not meet the requirements. Provided media that were sufficient and met two (2) of the three (3) characteristics. Fulfilled with 80 – 89% quality and accuracy. WEEK 5 Weekly Activities: Reading: ? Midterm exam will cover contents from chapters 1, 11, 12, 14 and 15 Assignments: ?

Complete Midterm Examination Assignment: Midterm Exam Students are to take the Midterm that covers the material in Chapters 1, 11, 12, 14 and 15. The Midterm is located in the course shell under the Week 5 tab. This is an open book, timed exam that can only be taken once with a time limit of four hours. The exam consists of a combination of true/false, multiple choice, and problem questions for a total of 40 questions. Each question is worth 5 points. MAT540 Student Version 1122 (11-29-2011) Final Page 11 of 19 WEEK 6 Course outcome in focus: ? Solve linear programming problems. Supporting topics: ? Model formulation ? Maximization model ? Graphical solutions of linear programming models ? A minimization model ? Irregular types of linear programming models ?

Characteristics of linear programming problems Weekly Activities: Reading: Chapter 2, Linear Programming: Model Formulation and Graphical Solution Assignments: ? Complete Week 6 Quiz Course Lectures: ? ? Lecture/discussion on Model formulation; maximization model Activity –Linear programming Model o What are some business uses of a linear programming model? Provide an example. Lecture/discussion on irregular types of linear programming models; characteristics of linear programming problems Activity – Characteristics of linear programming o In the graphical method, how do you know when a problem is infeasible, unbounded, or when it has multiple optimal solutions? o What are the essential ingredients of an LP model?

Why is it helpful to understand the characteristics of LP models? Lecture/discussion on Minimization model Activity – Minimization model o Distinguish between a minimization and maximization LP model. How do you know which of these to use for any given problem? ? ? ? ? Assignment: Quiz 3 Please take the quiz in the course shell for Week 6 that covers the material in Chapter 2. This is an open book, timed quiz that can only be taken once with a time limit of one hour. The quiz consists of a combination of true/false, multiple choice, and problem MAT540 Student Version 1122 (11-29-2011) Final Page 12 of 19 questions for a total of twenty questions.

Each question is worth 2 points. WEEK 7 Course outcome in focus: ? Create sensitivity analysis on linear programming model parameters. ? Use technology and information resources to research issues in Management Science. Supporting topics: ? Computer solution of linear programming problems ? Sensitivity analysis Weekly Activities: Reading: ? Chapter 3, Linear Programming: Computer Solution and Sensitivity Analysis Assignments: ? Complete Week 7 Case assignment Course Lectures: ? Lecture/discussion on Computer solution of linear programming problems Sensitivity analysis investigates how our decision might change given a change in the problem data.

Sensitivity analysis is a vital part of all spreadsheet modeling. In optimization modeling, some of the most valuable insights come not from the optimal solution itself, but from a sensitivity analysis around the optimal solution. As we will see, the special structure of linear programs gives rise to certain characteristic results. Compared to the Solver Sensitivity output, the Sensitivity Report is more precise but less flexible. The Sensitivity Report is more precise than Solver Sensitivity with respect to the question of where the decision variables change or where a shadow price changes. ? Activity – Discussion on shadow price o What does the shadow price reflect in a maximization problem?

Please explain o How do the graphical and computer-based methods of solving LP problems differ? In what ways are they the same? Under what circumstances would you prefer to use the graphical approach? Lecture/discussion on Sensitivity analysis Activity – Discussion on sensitivity analysis o How does sensitivity analysis affect the decision making process? How could it be used by managers? ? ? Assignment: MAT540 Student Version 1122 (11-29-2011) Final Page 13 of 19 Assignment #3: Case Problem “Julia’s Food Booth” Complete the “Julia’s Food Booth” case problem on page 109 of the text. Address each of the issues A- D according the instructions given. o (A) Formulate and solve an L. P. model for this case. (B) Evaluate the prospect of borrowing money before the first game. o (C) Evaluate the prospect of paying a friend \$100/game to assist. o (D) Analyze the impact of uncertainties on the model. The assignment will be graded using the associated rubric. Outcome Assessed: ? Create sensitivity analysis on linear programming model parameters ? Communicate issues in Management Science Grading Rubric for Assignment – Assignment #4 Case Problem There are 12 points in each of the five criteria for a total of 60 points possible Criteria 0 Unacceptable (0 points) Did not submit or LP model is not sufficiently attempted and does not demonstrate a. recognizable attempt to model this case.

Did not submit or did not solve the linear programming model accurately. Did not submit or did not evaluate accurately. 1 Developing (6 points) LP model is partially correct, but has errors in the objective function or constraints. Described with 70 – 79% accuracy, clarity, and completeness. Solved the linear programming model with 70 – 79% accuracy. Evaluated and explained with 70 – 79% accuracy. 2 Competent (9 points) LP model has objective function and most constraints correctly specified. Described with 80 – 89% accuracy, clarity, and completeness. Solved the linear programming model with 80 – 89% accuracy. Evaluated and explained with 80 – 89% accuracy. Exemplary (12 points) LP model has objective function and all constraints fully and correctly specified. Described with 90 – 100% accuracy, clarity, and completeness. Solved the linear programming model with 90 – 100% accuracy. Evaluated and explained with 90 – 100% accuracy. 1. Formulate an LP model for this case. (Part A). 2. Solve the linear programming model formulated in Criterion 1 (Part A) 3. Evaluate the prospect of borrowing money before the first game. (Part B). 4. Evaluate the prospect of paying a friend \$100/game to assist. (Part C) 5. Analyze the impact of uncertainties in the model. (Part D) Did not submit or did not evaluate accurately.

Did not submit or did not analyze accurately. Evaluated and explained with 70 – 79% accuracy. Analyzed the impact with 70 – 79% accuracy, logic, and completeness. Evaluated and explained with 80 – 89% accuracy. Analyzed the impact with 80 – 89% accuracy, logic, and completeness. Evaluated and explained with 90 – 100% accuracy. Analyzed the impact with 90 – 100% accuracy, logic, and completeness. WEEK 8 Course outcome in focus: ? Apply linear programming models to project management applications. Supporting topics: ? Product mix ? Diet ? Investment MAT540 Student Version 1122 (11-29-2011) Final Page 14 of 19 ? Marketing ? Transportation ? Blend ? Multiperiod scheduling ?

Data envelopment analysis Weekly Activities: Reading: ? Chapter 4, Linear Programming: Modeling Examples Assignments: ? Complete Week 8 Quiz Course Lectures: ? Lecture/discussion on how linear programming is used to solve various types of models. The types of examples are product mix examples, diet examples, investment examples, marketing examples, transportation examples, blend examples, multiperiod scheduling examples, and data envelopment analysis examples. Activity –Discussion on objective function o What is the relationship between decision variables and the objective function? o What is the difference between an objective function and a constraint?

Lecture/discussion on how we follow the same procedure: identify the decision variables, determine the objective function, and develop the model constraints. Activity – Discussion on applications of linear programming o Does the linear programming approach apply the same way in different applications? Explain why or why not using examples. ? ? ? Assignment: Quiz 4 Students are to take the quiz in the course shell for Week 8 that covers the material in Chapter 4. This is an open book, timed quiz that can only be taken once with a time limit of one hour. The quiz consists of a combination of true/false, multiple choice, and problem questions for a total of twenty questions. Each question is worth 2 points.

WEEK 9 Course outcome in focus: ? Solve integer programming problems. Supporting topics: ? Integer programming (ip) models ? Integer programming graphical solution MAT540 Student Version 1122 (11-29-2011) Final Page 15 of 19 ? Computer solution of integer programming problems Weekly Activities: Reading: ? Chapter 5, Integer Programming. Assignments: ? Complete Week 9 Quiz Course Lectures: ? Lecture/discussion on the three basic types of integer linear programming models. In a total integer model, all of the decision variables are required to have integer solution values. In a zero-one integer model, all the decision variables must have values of zero or one.

In a mixed integer model, some, but not all, of the decision variables are required to have integer solutions. Activity – Discussion on the difference between integer and linear programming o Explain how the applications of Integer programming differ from those of linear programming. o Why is “rounding-down” an LP solution a suboptimal way to solve Integer programming problems? ? Lecture/discussion on how to solve these different models, certain constraints must be specified as part of the model. For a total integer model, all decision variables must be designated as integer. For a zero-one integer model, the decision variables must be designated as integers, with the only possible values being zero and one.

Finally, for a mixed integer model, only those decision variables that must be integers are designated as integer values. The other decision variables can be designated as real, or non-integer, values. ? Activity – discussion on characteristics of integer programming problems o Explain the characteristics of integer programming problems. o Give specific instances in which you would use an integer programming model rather than an LP model. Provide real-world examples. Assignment: Quiz 5 Students are to take the quiz in the course shell for Week 9 that covers the material in Chapter 9. This is an open book, timed quiz that can only be taken once with a time limit of one hour.

The quiz consists of a combination of true/false, multiple choice, and problem questions for a total of twenty questions. Each question is worth 2 points. Online students are to complete the quiz by Sunday Midnight of Week 9. On-campus students are to complete this quiz before the Week 10 class meeting. WEEK 10 MAT540 Student Version 1122 (11-29-2011) Final Page 16 of 19 ? Course outcome in focus: ? Develop solutions for transshipment problems. ? Use technology and information resources to research issues in Management Science. Supporting topics: ? The transportation model ? Computer solution of a transportation problem ? The transshipment model ? Computer solution of a transshipment problem ? The assignment model Weekly Activities: Reading: ?

Chapter 6, Transportation, Transshipment, and Assignment Problems Assignments: ? Complete Week 10 Case Assignment Course Lectures: ? Lecture/discussion on transshipment models being an extension of the transportation model where intermediate points, known as transshipment points, are added between sources and destinations. Activity – Discussion on transshipment problems o Can we apply transshipment models to inventory applications? Why or why not? o Is the transportation model an example of decision making under certainty or decision making under uncertainty? Why? Lecture/discussion on assignment problem being a special form of a linear programming model in which all supply and demand values equal one.

Activity – Discussion on transportation problems o o Assignment: Assignment #4: Case Problem “Stateline Shipping and Transport Company” Read the “Stateline Shipping and Transport Company” Case Problem on pages 273-274 of the text. Analyze this case, as follows: 1. In Excel, or other suitable program, develop a model for shipping the waste directly from the 6 plants to the 3 waste disposal sites. MAT540 Student Version 1122 (11-29-2011) Final Page 17 of 19 Explain the assignment model and how it facilitates in solving transportation problems. What benefits would be gained from using this model? ? ? ? 2. Solve the model you developed in #1 (above) and clearly describe the results. 3.

In Excel, or other suitable program, Develop a transshipment model in which each of the plants and disposal sites can be used as intermediate points. 4. Solve the model you developed in #3 (above) and clearly describe the results. 5. Interpret the results and draw conclusions that address the question posed in the case problem. What are the limits of the study? Write at least one paragraph. There are two deliverables for this Case Problem, the Excel spreadsheets and an accompanying written description/explanation. Please submit both of them electronically via the dropbox. The assignment will be graded using the associated rubric. Outcome Assessed: ? Develop solutions for transshipment problems. Communicate issues in Management Science Grading Rubric for Stateline Shipping & Transport Case Problem There are 12 points in each of the five criteria for a total of 60 points possible 0 Unacceptable (0 points) Did not submit or the objective function and/or constraints are specified with less than 70% accuracy. Criteria 1 Developing (6 points) The objective function and constraints are specified and described with 70 – 79% accuracy. The model is solved, but its validity is questionable or it is incorrectly described. The objective function and constraints are specified and described with 70 – 79% accuracy. The model is solved, but its validity is questionable or it is incorrectly described. There are errors in interpreting the results; or inappropriate conclusions are drawn; or this is not clearly communicated. 2 Competent (9 points)

The objective function and most or all constraints are specified correctly and adequately described. The model is solved and the results are mostly valid and mostly correctly described. The objective function and most or all constraints are specified correctly and adequately described. The model is solved and the results are mostly valid and mostly correctly described. Results are interpreted in a mostly correct manner; conclusions drawn are mostly appropriate; and communicated in a mostly clear manner. 3 Exemplary (12 points) The objective function and all constraints are specified correctly in the model and clearly described The model is solved and the results are valid and correctly described.

The objective function and all constraints are specified correctly in the model and clearly described The model is solved and the results are valid and correctly described. Results are correctly interpreted; appropriate conclusions are drawn and communicated clearly. 1. Develop a transportation model for shipping from the 6 plants directly to the 3 disposal sites. Describe and implement the model. 2. Solve the model given in 1 and describe the results. Did not solve the model or adequately describe the results. 3. Develop a transshipment model in which each of the plants and disposal sites can be used as intermediate points. 4. Solve the model given in 3 and describe the results. Did not submit or the objective function and/or constraints are specified with less than 70% accuracy.

Did not solve the model or adequately describe the results. 5. Interpret the models and draw conclusions Did not complete the assignment or interpretation and/or conclusions drawn are invalid and/or not intelligibly communicated. WEEK 11 Weekly Activities: Reading: ? Final exam will cover contents from chapters 1, 2, 3, 4, 5, 6, 11, 12, 14 and 15 MAT540 Student Version 1122 (11-29-2011) Final Page 18 of 19 Assignments: ? Complete Final Examination Assignment: Final Exam Students are to take the Final Exam that covers the material in Chapters 1, 2, 3, 4, 5, 6, 11, 12, 14 and 15. The Final exam is located in the course shell under the Week 11 tab.

This is an open book, timed exam that can only be taken once with a time limit of four hours. The exam consists of a combination of true/false, multiple choice, and problem questions for a total of 40 questions. Each question is worth 5 points. ASSIGNMENT OUTLINE AND GRADING Assignment Type Discussions = 9 x 20 points = 180 points 18% Case Assignments = 3 x 60 = 180 points 18% Quizzes = 5 x 40 = 200 points 20% Midterm Exam = 1 x 200 = 200 points 20% Internet Field Trip = 1 x 40 = 40 points 4% Final Exam = 1 x 200 = 200 points 20% Value Grading Scale 90-100 80-89 70-79 Below 70 A B C F MAT540 Student Version 1122 (11-29-2011) Final Page 19 of 19

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