Course Information for OPRE 315:
Business Applications of Decision Science

This is a Web-text companion site for the Web-enhanced textbooks:
Success Science    Leadership Decision Making    Linear Programs (LP)
LP Applications   Risky Decisions    Queueing and Simulation    Course E-Labs



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The MENU:
1. Any Question?
2. Short Version of the Course Information (Word.Doc)


I am looking forward to working with you and hope that you will find the course both enjoyable and informative.
Professor Hossein Arsham   

To search the site, try Edit | Find in page [Ctrl + f]. Enter a word or phrase in the dialogue box, e.g. "analytical geometry" or "probability" If the first appearance of the word/phrase is not what you are looking for, try Find Next.

         MENU

  1. Welcome Message
  2. Academic Policy Statement
  3. Tutorial Help for This Course
  4. Course Description
  5. Course Structure, Ingredients & Learning Objects
  6. The School's Mission and the Course Objectives
  7. Learning Style for this Course
  8. What Math Do I Need for this Course?
  9. Required Textbook, Recommended Readings, & Computer Package
  10. Computer-assisted Learning: WinQSB Package
  11. Course Requirements, Grading Criteria & System
  12. Instructions for Homework Assignment
  13. Homework Assignment to Do Before Each Class Meeting and Sample Tests


Academic Policy Statement

The University of Baltimore comprises a community of students, faculty, administrators, and staff who share a commitment to learning. As the practice of academic honesty is essential to learning, the university has established a policy for academic honesty. It can be found online in the Student Handbook at www.ubalt.edu/studentlife.

All members of our community share responsibility for actively fostering academic honesty, actively discouraging academic dishonesty, and engaging in ongoing discussion of activities that may violate the spirit of honesty. Although the academic integrity policy places primary emphasis on fostering honesty, it also provides clear consequences for behavior that violates the policy, together with fair procedures for judging alleged cases of dishonesty.


Tutorial Help for This Course

You may seek services (free-of-charge) tutorial help from the Achievement and Learning Center (ALC) located at Academic Center (AC) Room AC 113 or by sending an email to: alc@ubalt.edu or by calling at (410) 837-5385. Professor Yoosef Kkhadem (ykhadem@ubalt.edu) is the Coordinator of Stat Service at ALC. He is knowledgeable, and has both experienced and patient. We are fortunate to have him as the tutor for this course.
If you do well in this course and would consider tutoring students in future semesters, please send an Email to the Academic Resource Center.


Dear Student and Decision-Maker

Welcome to: Decision Science: Making Good Strategic Decisions

I look forward to working with you and hope that you will find the course both enjoyable and informative.

In our increasingly complex world, the tasks of the decision-makers are becoming more challenging every day. The decision-maker must respond quickly to events that take place at an ever-increasing speed. A decision-maker must incorporate an often bewildering array of choices and consequences into his or her decisions.

The Web site for this course was designed and created for you. No one need be ashamed of what he or she does not know or how long it takes to master new information. Learning by the Web-enhanced course material can be self-paced and non-judgmental. Using advantages of this technology to expand learning opportunities is especially crucial because we live in a time when learning is a necessity and no longer a luxury.

At one time, it was sufficient for a firm to produce a quality product. As competition grows in today's market, simply producing a quality product is not sufficient. Today, a firm must produce a quality product at less cost than its competitors and simultaneously manage inventory, warehouse space, procurement requirements, etc. In the future, still greater demands will be placed upon decision-makers.

A manager makes many decisions everyday. Some decisions are routine and inconsequential, while others may impact the operations of a firm. Some decisions cause a firm to lose or gain money or determine whether goals are reached. The field of Decision Science (DS), known also as Operations Research (OR), Management Science (MS), and Success Science (SS), has helped managers develop the expertise and tools to understand decision problems, put them into mathematical terms and solve them.

Many tools and techniques help individuals and organization make better decisions. This course provides decision makers and analysts the tools that provide a logical structure to understand the mathematical techniques to solve formulated (i.e. modeled) problems. The primary tools are linear programming and decision analysis, which provide structure and value in helping define and under-stand a problem. In this course you will learn OR/MS/DS/SS methodologies to determine optimal strategic solutions to described problems. Personal Computers allow application of these techniques even in the small business environment. Finally, a clear understanding of a general approach to problem solving enables you to use other applied decision-making and planning techniques in this course.

Since the strategic solution to any problem involves assumptions, it is necessary to determine how much the strategic solution changes when the assumptions change. You learn this by performing "what-if" scenarios or sensitivity analysis.

Preparation for management, whether it is related to technology, business, production, or services, requires knowledge of tools, which aid in determining feasible and optimal policies. In addition to communication and qualitative reasoning skills, enterprises wishing to remain competitively viable in the future, need decision support systems to help them understand the complex interactions between all components of an organization's internal and external system. Such components are found in environmental design, transportation planning and control, facilities management, military mission planning and execution, disaster relief operations, investment management, and manufacturing operations.

An organization, like other organisms, must keep itself in a state of homeostasis--subsystems regulate one another so none of the parts is ahead or behind the system as a whole. This interaction is not trivial; mathematical modeling assists in understanding these fundamental relationships. OR/MS/DS/SS concepts focus on communication of results and recommended action. This helps build a consensus concerning the possible outcomes and recommended action. The decision-maker might incorporate other perspectives of the problem, such as culture, politics, psychology, etc., into the management scientist's recommendations.

The creation of Decision Science software is one of the most important events in decision-making. OR/MS/DS/SS software systems are used to construct examples, to understand existing concepts, and to find new managerial concepts. New developments in decision-making often motivate developments in solution algorithms and revisions of software systems. OR/MS/DS/SS software systems rely on a cooperation of OR/MS/DS/SS practitioners, algorithms designers and software developers.

This course overviews the major quantitative modeling tools successfully used to model the complex interactions described above. Although not exhaustive, this course provides framework for further study. The following tools will be studied: analytically based solutions to math models, linear programming, decision theory, integer programming and network models Decision Science encompasses many disciplines of study because decision-making is a central human activity. Appreciation of decision making is wonderful: it makes what is excellent in this thinking process belongs to you as well.

Just like you, most of your classmates are employed full time. They are engineers, doctors, lawyers, and other professionals. You and your classmates want to learn the business side of their professions. It is important to learn the language of the managers to overcome communication barriers. For example, engineers will learn how to translate "precision" into extra dollars in earning/saving.

In each class I teach, there are some students who find it difficult to rethink and re-evaluate their pre-conceived ideas. In decision-making, one must have an open-mind to be able to think differently and to see from many perspectives. University classrooms provide the environment for debate and the exchange of ideas. Open-mindedness is the main requirement in achieving the ultimate goal of education, which is to be able to think for yourself. Change of opinion is often the progress of sound thought and growing knowledge.

Upon completion of this course, you may find that it "validates" what you think about making good strategic decisions and causes a peace of mind. The contents of this course will help you to systematize what you already know from your own professional experience.

For my teaching philosophy statements, visit the Web site On Learning & Teaching.

Feel free to contact me via phone, faxes, or email. There is a lot of material to cover, so let's start now!

Course Description

A study of a range of problems and applications to managerial decision making using scientific and analytical methodology. Topics include an in-depth understanding of linear programming and sensitivity analysis and an introduction to decision analysis and Queueing and Simulation. Problem recognition, model building, model analysis and managerial implications are the primary objectives with special emphasis on understanding the concepts and computer implementation and interpretation.
Prerequisites: MATH 107, and OPRE201.


Course Structure, Ingredients & Learning Objects

Course Structure: Your course materials are divided into seven ordered sections:

(For your weekly homework, visit the Homework Assignment section on this site).

Course Ingredients: The Course Ingredient Components Include:

  1. A set of Technical Keywords and Phrases,
  2. A Collection of Problem-Solving Methodologies, and
  3. Managerial Interpretations, Their Implications and Applications.

Learning Objects:

  1. Textbook: Your textbook is the main source reading and the exercise before each class meeting.
  2. Lecture Notes: Lecture notes are not your textbook substitute. They are designed to meet your needs, as I perceive while lecturing.
  3. Live Lectures & Handouts: The lectures are the bases of your interactions as a learning process, with your classmates and me.
  4. Computer Assisted Learning: My teaching style deprecates the 'plug the numbers into the software and let the magic box work it out' approach. The software is an effective tool for experimentation in serving your needed "hands on experience" for understanding the managerial implication of the concepts for yourself.

I am sure that your careful readings and effective use of the above learning objects, provide various perspectives, create a deep understanding of the topic, together with the wholeness and manifoldness of this course.


Required Textbook, Recommended Readings, & Computer Package

Required Textbook: Introduction to Management Science,
by Bernard W. Taylor
Prentice Hall, 11th edition, 2013,
ISBN-10: 0132751917
ISBN-13: 9780132751919

Your textbook is available at the UB Bookstore, (410) 837-5604.

The textbook chosen for this course is excellent. It is a modern, well-written and clear account of the issues facing decision makers doing business. It is easy to read, has broad coverage and is eminently suitable for self-study with many applications.

Notice that the Topics Web site units contain my weekly lecture notes. The purpose of these units is not to replace your textbook. Rather, its purpose is to provide you with other perspectives on the same topics to enhance your deep understanding.

Recommended Readings: I strongly recommend a reading of the following books:

Linstone H., Decision Making for Technology Executives: Using Multiple Perspectives to Improved Performance, Artech House, SBN: 0890064032, 1999. A copy of this book is also available as "a reserve item" for your use upon request at the Langsdale Library.

Mingers J., and A. Gill, (Eds.), Multimethodology: The Theory and Practice of Integrating Management Science Methodologies, Wiley & Sons, 1997. A copy of this book is also available at the Langsdale Library.

Further Readings: There are some Decision-Making textbooks that you may find helpful. They are located at the Langsdale Library:

Decision-Making Books:

  1. Decision sciences: An Integrative Perspective
    By C. Kunreuther, Paul J.H. Schoemaker
    Cambridge University Press, 1993
    Location: HD30.23 .K46

  2. Management science: An Aid for Managerial Decision Making
    By M. Austin, James R. Burns
    Macmillan Press, 1995
    Location: T56 .A87

  3. Management Science: Decision Making through Systems Thinking
    By Hans G. Daellenbach, Donald C. McNickle
    Macmillan Press, 2005
    Location: T57.6 .D32

  4. Management Science for Decision Makers
    By Larry M. Austin, Parviz Ghandforoush
    West Pub. Co., c1993
    Location: T56 .A88

  5. Management Science for Decision Makers
    By Larry M. Austin, Parviz Ghandforoush
    West Pub. Co., 1993
    Location: T56 .A88

  6. Management Science Knowledge: Its creation, Generalization, and Consolidation
    By Arnold Reisman
    Quorum Books, 1992
    Location: T56 .R542

  7. Operations research: A Fundamental Approach
    By James E. Shamblin, G. T. Stevens, Jr
    McGraw-Hill, 1994
    Location: T57.6 .S48

  8. Operations Research: Applications and Algorithms
    By Wayne L. Winston
    Duxbury Press, 1997
    Location: QA402.5 .W54


Some other Decision Science textbooks are located on the following stacks: HD28, HD30, HD31, QA402, and T56, also Decision making Video: Values and goals, Alternatives and information, Outcomes and actions, HD30.23.D43 1987 VC, at the Langsdale Library.

Computer Package: The WinQSB is available on the the University NT server (free-of-charge). Unfortunately, one cannot access the system remotely. To use the system you need an NT account. To obtain your NT account see the Technical Assistance (TA) at the lower level of Business Center. After obtaining your username and a password then you can access the NT system. To reach the QSB, click on Start, choose the Business School Applications, then click on the Shortcut to QSB, or QSB. Then, pick-up the application you wish. All WinQSB applications are therein.


Course Requirements, Grading Criteria & System

Course Requirements & Grading Criteria
Readings & homework 20%
First examination 40%
Final examination 40%

Course Grading System
90 - 100 80 - 89 70 - 79 65 - 69 60 - 64 otherwise
A
B +
B
C +
C
F


General Instructions

  1. Write everything you know about the topics, one by one.

  2. When you can't think of anything more, give yourself time to look for topics and details you may have missed.

  3. Ask yourself, is there anything else I may have missed? Be as inclusive as possible.

  4. Summarize your writing to create fewer pages.

  5. Re-organize to make even fewer pages.

  6. Ask, How do the topics fit together? What elements are related and how?

  7. Ask, What is the significance for me? What can I do with it? What are the implications?

  8. Go back to step 3, until you have as few pages of summary as possible.

The above process helps to crystallize your mind to be reflective and responsive to questions posed about topics you've learned in this course and reinforces the topics in your mind.

To view a Summary-Sheet for the first test, prepared by one of your classmates, click here. If you think you have prepared a better one, kindly send it to me via an attached email. Thank you.


What Math Do I Need for this Course?

Don't Panic, high school math will suffice! There will be some refreshers. The following sites may help:

High school math refresher.


Homework Assignment to Do Before
Each Class Meeting and Sample Tests

Please read and follow the Instructions for your homework assignment. Thank you.

We will proceed in the following sequence (Not a weekly-schedule of topics).

  1. Reading Assignment and Essay: Read the Preface, the Management Science Modeling (Ch. 1). Read also the introductory sections of all the chapters (i.e., sections 1 of all chapters) in your textbook. This is a good way to get a grip on your textbook and the concepts contained therein.
    Visit the main Web site of this course and go over the title of the topics therein. Visit the following Web sites:
    INFORMS
    Decision Sciences Institute
    OR Page
    Operational Research Society

    After you did your reading assignment, then write a 2-page essay (format-free) entitled: "What is Applied Management Science?" Your essay should, among others, address some of the following questions:


  2. Analytical Geometry Review: Read Ch. 2, the course lecture notes and then Formulate (do not solve) Problem 2.7 (i.e., Chapter 2, Problem 7, Wilson Manufacturing Decision, on page 103) as a linear program (LP).
    I do recommend refreshing your knowledge about solving systems of equations by e.g., visiting the Web site Solving System of Equations.

    Visit the following Web site:
    The Zero Saga & Confusions With Numbers

  3. Linear Programming (LP): Graphical Solution Algorithms, Read Ch. 2 and the course lecture notes. Do all parts of problem 2.7, with a detailed step-by-step description of the graphical method, using graph paper (Word.Doc , graph paper (PDF). This part of assignment, makes one conscious about what one does.

  4. Computer Implementation: Solve problem 2.7 by
    the WinQSB OR
    Solving Wilson Problem by Excel and Excel Solver for General Linear Programs
    (I recommend watching for learning: Excel Videos for LP)

    Then compare the results with your graphical solution.

    Unfortunately, in some browsers the Graphical Methods of WinQSB, or EXcel may not be available. However, one may, e.g., use the following JavaScript instead.

    The LP Grapher

    Instead of WinQsb, you may use: Linear Program Solver

  5. Sensitivity Analysis: Review the Sensitivity Analysis section of the course lecture notes. Apply the right-hand-side (RHS) value and coefficients of the objective function (known as the cost coefficients, because historically during World War II, the first LP problem was a cost minimization problem) sensitivity range to problem 2.7 in Ch. 2, computer implementation together with managerial interpretations of the computer solution. Construct the dual problem, solve it and then provide economical interpretations for the dual and its solution. To construct the dual of a given problem by using WinQSB, click on Format, then select "Switch to the Dual Form".

    As you know by now, this course has three ingredients: A set of Technical Keywords and Phrases, A Collection of Problem-Solving Algorithms, and Managerial Interpretations, and the most important of all their Implications and Applications to Business Decision-Making. As I pointed out this course is not about say, linear programming (LP), we are using LP as an application and as a tool. Since you have mastered, the Keywords & Phrase, and Techniques, now we are able to concentrate on the Managerial Business Decision-Making Process. The lecture note section on Managerial Interpretation of the WinQSB Combined Report deals with how to interpret and describe the computational results in computer output such as, the optimal strategic solution, sensitivity ranges, shadow prices, and other useful information for the decision-maker.

    Perform some "what-if" scenarios analysis on Problem 2.7. That is, use your computer software package to do some numerical experimentation on variations of Problem 2.7. Again, this computer-assisted learning assignment provides a "hands-on" experience, which will enhance your understanding of the technical concepts, involved in various topics of controlling the problems, which we have covered. This computer-assisted learning concepts provides a "hands-on" experience which will enhance your understanding of the technical concepts involved in various topics of sensitivity analysis that we have covered.

  6. Integer LP Applications: Formulation and Solution Read What Can Go Wrong in Integer Programming? and Chs. 2, and 3. Formulate problems 2.33 and 2.34, and use the WinQSB package to find the optimal solutions with some managerial explanation on the output for each problem.

    Doing Integer LP by Excel Solver: Using the Constraint menu, for the LP Problem, select Normal Constraint and then the icon for “< = “ to obtain the Add Constraint window. Then we can designate any variable (e.g. , inter the variable, say $B$5 in the Cell Reference) as Integer in the Add Constraint window.

    For example, in the Wilson problem if you change cell F7 to 3299 sq ft. Baseball dozens(B4) and softball dozens(C4) come up to 209.5 and 375.25 respectively. Then when you change B4 and C4 to int, the answer comes up to 211 and 374. When you change to Binary Cells C4 and B4 go to 1 if any anser is greater than 0. They go to 0 if the answer is 0.

    Check your formulations with those one page 628-629 before using your software.

    Visit the following Web site:
    A Tutorial on Integer.

  7. Widely Used LP Business Applications: The Network Models Read Ch. 4, and the course lecture notes. Solve at least any two of the following problems 4.1, 4.2, 4.6, 4.7, and 4.9 by implementing them on WinQSB, provide your managerial interpretation of the optimal solution for each problem.
    You may ask what are the Managerial Interpretations?

    Managerial Interpretations: The decision problem is stated by the decision-maker often in some non-technical terms. When you think over the problem, and finding out what module of the software to use, you will use the software to get the solution. The solution should also be presented to the decision-maker in the same style of language, which is understandable, by the decision-maker. Therefore, just do not give me the printout of the software. You must also provide managerial interpretation of the solution in some non-technical terms.

    Warning: Computer solutions for the network and integer problems are valid, however the produced sensitivity results may not be valid. This is due to the facts that, among other things, these problems are Integer-LPs. Moreover, in the case of network models anyone constraint in any of these models is always redundant. Therefore, simply ignore the sensitivity analysis of the printouts.

  8. Review and Preparation for Exam: Homework: Prepare your summary-sheets Your Exams are 2-hours long, in-class, closed book and closed-notes. You may bring a few prepared summary-sheets.

    Preparation for the Exam: Your preparation is a very important undertaking in terms of integrating what you have learned each week in order to see the whole picture and inter-connectivity of the topics.

    To prepare yourself for the actual test, you are advised to review all the topics we have covered, to review past homework assignment, and then prepare your own few pages of a summary sheet. The process of producing a summary sheet, helps you to crystallize your mind to be reflective and responsive to any question posed to you about the topics you've learned in this course, it also helps you to reinforce the wholeness of the topics in your mind.

    To view a Summary-Sheets prepared by one of your classmates, click here. If you think you have prepared a better Summary-Sheets, kindly send it to me via an attached email. Thank you.

    Exercise Your Knowledge on this Past Exam:

    Past Exam (Word.Doc).

  9. First Examination: November 17 (tentative) Read the Examination Facts. The main purpose of taking the examinations is to find out how reflective your mind is in answering a set of questions correctly. The objective is to maximize the number of correct solutions, subject to a limited time constraint (a 2-hours session).

  10. Decision Analysis: Read Ch. 6 and the course lecture notes. Do problems 6.1, and 6.2 by hand and WinQSB applications.

    How stable is your decision? The computer packages such as your WinSQB, are necessary a very helpful tools for the decision maker in performing stability and sensitivity aspects of the decision whenever there is uncertainty in the payoffs and or in assigning probabilities in any decision analysis.

  11. Probabilistic Models: Re-read Ch. 6 and the course lecture notes, Queueing and Simulation. Do problems 6.3, 6.4, 6.5, and 6.34 by hand and WinQSB applications (if available).
    As a cautious note, you may experience some difficulties in comprehending the decision analysis problems, this is true for everyone while translating the way the problems are worded and the type of questions that are asked. Therefore, the most difficult part of decision analysis is the translation of the problem. Here are my suggestions: Read the problem may time, slowly. I suggest also drawing a decision tree to start with, then read the problem few time to modify the tree. Remember that, the mathematical representation of a decision analysis problem is the decision tree. .-->

  12. Decision Analysis: Read Ch. 6 and the course lecture notes. Do problems 6.1, and 6.2 by hand.

  13. Probabilistic Models: Re-read Ch. 6 and the course lecture notes. Do problems 6.3, 6.4, 6.5, and 6.34 by hand.
    As a cautious note, you may experience some difficulties in comprehending the decision analysis problems, this is true for everyone while translating the way the problems are worded and the type of questions that are asked. Therefore, the most difficult part of decision analysis is the translation of the problem. Here are my suggestions: Read the problem may time, slowly. I suggest also drawing a decision tree to start with, then read the problem few time to modify the tree. Remember that, the mathematical representation of a decision analysis problem is the decision tree.

  14. Review and Preparation for Final Examination: Read the Examination Facts.

    To view a Summary-Sheets on Decision Analysis, click here, and here for more numerical examples.

    Exercise Your Knowledge on this Past Final Exam:

    Past Final Exam (Word.Doc)

  15. Final Examination is a comprehensive one, given on December 15, 5:30 PM: Read the Examination Facts.


         Instructions for Homework Assignment


Learning Style For This Course

This course requires a particular learning style known as learning-to-learn. Effective and efficient learning includes completing weekly homework assignment and learning from feedback. Knowledge conquered by thinking for yourself becomes a possession -- a property entirely our own.

Unfortunately, most classroom courses are not learning systems. Instructors attempt to help their students acquire skills and knowledge with lectures, tests and memorization. Instructors "tell," which doesn't translate into usable skills. We learn by doing, failing and practicing. Computer assisted learning serves this purpose.

The change in learning in this course over the years is less emphasis on strategic solution algorithms and more on modeling processes, applications and software. This trend continues as more students with diverse backgrounds seek Business degrees without too much theory and mathematics. Our approach is middle-of-the-road: no excess of math or software. We learn how to formulate problems prior to software usage. You should learn how to model a decision problem, first by hand and then by using software. The software should be used for two purposes:

  1. Computer-assisted learning concepts and techniques, and

  2. For large problems that are too difficult to solve by hand.

What are the most critical challenges in learning for this course?

  1. To refresh your high school math including linear algebra, basic statistics, and probability.

  2. To learn the new technology, mainly the use of software within a reasonable amount of time. The learning curve of the software we will be using is very sharp.

  3. To link the course materials with other courses in your Business program.

  4. What is Management Science? A rational, structured approach to problem solving. It is the study of developing procedures that are used in decision-making and planning. An objective measure of performance must be identified to measure success. The objective must represent the decision-makers goal and serve as a starting point for developing a model for the problem.
  5. The context of modeling: What is a management science model? There are two types of models: Deterministic and Probabilistic. Deterministic modeling is linear programming for optimization while decision analysis is a probabilistic modeling tool used for problems under uncertainty.

  6. Model design, selection and setup: This includes justifying model selection (validation), setting assumptions, parameters, advantages and limitations of various models, considering the effects of data quality and accessibility, regulations, implicit versus explicit assumptions, computer models (verification), and sensitivity analysis.

  7. Input data selection and analysis: How to find data and the balance between quality, accessibility, credibility, and relevance. How to evaluate data quality and understand its impact.
  8. Analysis of results: How to tell if results are reasonable, sensitivity of output to changes in input, recognition of the useful life of a model.
  9. Cases and applications: Word Problem Formulation, Pure Integer/ Mixed-integer Linear Programs, Transportation Problem, Assignment Problem, Shortest Path Problem, Max Flow Problem, Critical Path Method in Project Management, Decision Analysis Cases.

  10. Communication: Clearly and accurately communicate the process and result by understanding the nature of the audience, effects of standards and regulations, use of appropriate format and media and maintenance of internal documentation.

It is axiomatic that if learning occurs, there is change in you. Change might occur in your attitude, thinking, beliefs and/or behavior. Something will have changed or else learning simply did not occur. I am sure you will be enthusiastic about the topics covered in this course throughout the semester and beyond. Enthusiasm is one of the most powerful engines of success; enthusiasm changes problems into challenges. When you study for this course, put your whole mind into it. Stamp your work with your own personality when it is submitting. Be active, energetic, honest, and remember: learning-to-learn was never achieved without enthusiasm.


The School's Mission and the Course Objectives

Merrick School of Business Mission Statement: Our mission is to prepare our diverse mix of students in collaboration with the business community to succeed in a dynamic global economy. The goal is to make excellence accessible. We achieve our mission by:

Course Objectives: What Do I Learn?

Preamble: The Merrick School of Business is strongly committed to the improvement of student learning through the assessment of our undergraduate and graduate degree programs. As part of this process, rubrics have been developed to provide students with qualitative guidance about what level of performance meets, exceeds or falls below expectations for specific skills and learning objectives. Students are encouraged to review the rubrics located on the Merrick School website Merrick School of Business Assessment to understand expectations for effective communication, analytical and problem solving skills, ethical reasoning, and other skills necessary in business. There are varieties of sources in helping you to understand the foundation of decision making. Each of the following items provides you with different perspectives on our weekly topics.

The general objective of the course is to assist you in understanding and applying the general process of structural decision-making and its components.

Notice that, although we have multiple overall objectives for this course, this does not make our task a "multiple-objective problem", since there is no maximization nor minimization statement in any of our objectives.

Upon completing this course, you should be able to:

  1. Explain an analytical model for structuring and analysis of business decision problem, and queueing and simulation models.
  2. Discuss the complimentary nature of the rational and behavioral approaches to decision-making.
  3. Discuss the usefulness and the limitations of Management Science.
  4. Use sensitivity analysis to gain insights of the optimal decision making in response to the changes in the decision-maker's environment.
  5. Understand and apply the general process of structural decision-making and its components to solve their business problem.
  6. Apply Management Science to case studies to find solutions to real life business problems including those in global environment.
  7. Communicate effectively the analysis and results of a business decision problem to the decision-maker.
  8. Discuss the ethical dimensions by addressing integrity issues in data collection and consideration of the human-side of modeling process.
  9. Learn the concepts and techniques of Management Science by doing weekly homework assignments and learning from my feedback.
  10. Learn and apply new technologies, including commercial software packages, to aid business decision-making and planning, and to obtain timely solutions to decision problems.


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Decision Science: Making Good Strategic Decisions
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