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I am looking forward to working with you and hope that you will find the course both enjoyable and informative.
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MENU
- Welcome Message
- Academic Policy Statement
- Tutorial Help for This Course
- Course Description
- Course Structure, Ingredients & Learning Objects
- The School's Mission and the Course Objectives
- Learning Style for this Course
- What Math Do I Need for this Course?
- Required Textbook, Recommended Readings, & Computer Package
- Computer-assisted Learning: WinQSB Package
- Course Requirements, Grading Criteria & System
- Instructions for Homework Assignment
- 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).
- The Foundation of Decision-Making Process: When one talks of "foundations", usually it includes historical, psychological, and logical aspects of the subject.
- Overcoming Serious Indecisiveness: Behavioral aspect of making hard decisions and how modern managers think on tough decisions and opportunities.
- Quantitative Tools for Modeling: Our high-school math review including Analytical Geometry, and Working with Numbers.
- Deterministic Modeling: How to get what you expect. Course materials in this part will be presented in the context of a production and operations management applications with economics implications of the optimal decision. Our case study is the decision problem of allocating scarce resources among competitive means.
- Deterministic Models: It includes the linear optimization of Network Models and Integer Programs.
- Probability and Statistics for Modeling Risky Decisions: The needed review of your Business Statistics.
- Probabilistic Modeling: Decision making under uncertainty, i.e., what you expect you may not get. Materials in this part of the course will be presented in the context of financial portfolio selections, and marketing a new product decisions. An introduction to Queueing and Simulation.
Course Ingredients: The Course Ingredient Components Include:
- A set of Technical Keywords and Phrases,
- A Collection of Problem-Solving Methodologies, and
- Managerial Interpretations, Their Implications and Applications.
Learning Objects:
- Textbook: Your textbook is the main source reading and the exercise before each class meeting.
- Lecture Notes: Lecture notes are not your textbook substitute. They are designed to meet your needs, as I perceive while lecturing.
- Live Lectures & Handouts: The lectures are the bases of your interactions as a learning process, with your classmates and me.
- 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:
- Decision sciences: An Integrative Perspective
By C. Kunreuther, Paul J.H. Schoemaker
Cambridge University Press, 1993
Location: HD30.23 .K46
- Management science: An Aid for Managerial Decision Making
By M. Austin, James R. Burns
Macmillan Press, 1995
Location: T56 .A87
- Management Science: Decision Making through Systems Thinking
By Hans G. Daellenbach, Donald C. McNickle
Macmillan Press, 2005
Location: T57.6 .D32
- Management Science for Decision Makers
By Larry M. Austin, Parviz Ghandforoush
West Pub. Co., c1993
Location: T56 .A88
- Management Science for Decision Makers
By Larry M. Austin, Parviz Ghandforoush
West Pub. Co., 1993
Location: T56 .A88
- Management Science Knowledge: Its creation, Generalization, and Consolidation
By Arnold Reisman
Quorum Books, 1992
Location: T56 .R542
- Operations research: A Fundamental Approach
By James E. Shamblin, G. T. Stevens, Jr
McGraw-Hill, 1994
Location: T57.6 .S48
- 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%
| 90 - 100 | 80 - 89 | 70 - 79 | 65 - 69 | 60 - 64 | otherwise |
General Instructions
Your examinations have similar format as the Sample Exams, consisting of two parts:
You do not have to type your homework assignments; you may save some times in spending more on learning than typing. In this case please, please hand-in your eligible homework on time.
Homework Due Date: Meeting deadlines and even sending me material before deadlines are very important, since you will be engaging in group learning activities where time is crucial. So you should make every effort to complete your work on time. Therefore, late homework submissions carry no credit at all.
As you used to do experiments in physics labs to learn physics, computer-assisted learning enables you to use any online interactive tools available on the Internet to perform experiments. The purpose is the same, i.e., to understand managerial concepts such as the sensitivity analysis in your decision-making, by using applets which, are entertaining and educating.
The appearance of computer software, Java Applets, Online computation is one of the most important events in the process of teaching and learning concepts in model-based decision making courses. These tools allow you to construct numerical examples to understand the concepts, and to find their significance for yourself.
Computer-assisted learning is similar to the experiential model of learning. The adherents of experiential learning are fairly adamant about how we learn. Learning seldom takes place by rote. Learning occurs because we immerse ourselves in a situation in which we are forced to perform. You get feedback from the computer output and then adjust your thinking-process if needed.
Since you are allowed ONLY to use your own Pre-Prepared Summary-Sheets for Exam. Read carefully the Summary-Sheets for the Exam on this page, while preparing one for the test.
You will also need graph paper (Word.Doc) , graph paper (PDF), a scientific calculator, and a blue book (available at the Bookstore).
When taking your exam, present your work in detail. This will allow me to give partial credit.
The exams are not in any particular format so expect both standard numerical problem solving and conceptual type questions. The exams will test your understanding of the material covered in this course. 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). Samples of past exams are available on this Web site for inspection.
Click here to see a Summary-sheet prepared by one of your classmates. If you think you have prepared a better one, kindly send it to me via an attached email. Thank you.
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:
Homework Assignment to Do Before
Each Class Meeting and Sample TestsPlease read and follow the Instructions for your homework assignment. Thank you.
We will proceed in the following sequence (Not a weekly-schedule of topics).
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:
Visit the following Web site:
The Zero Saga & Confusions With Numbers
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.
Instead of WinQsb, you may use: Linear Program Solver
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.
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.
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.
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.
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.
To view a Summary-Sheets on Decision Analysis, click here, and here for more numerical examples.
Part II: Compute Implementation (whenever applicable) using QSB package, Excel, JavaScripts, etc., since without a computer package one cannot perform any realistic decision-making process and analysis (20 points).
You do not have to type your homework assignments; you may save some times in spending more on learning than typing. In this case please, please hand-in your eligible homework on time.
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:
- Computer-assisted learning concepts and techniques, and
- For large problems that are too difficult to solve by hand.
What are the most critical challenges in learning for this course?
- To refresh your high school math including linear algebra, basic statistics, and probability.
- 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.
- To link the course materials with other courses in your Business program.
- 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.
- 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.
- 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.
- 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.
- 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.
- 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.
- 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:
- Creating and delivering a leading edge curriculum with practical learning experiences in innovative and flexible ways;
- Maintaining intellectual currency through scholarship on business theory, practice and education; and
- Providing expertise to the private and public sectors as well as the academic community.
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: