Managerial Decision Modeling with Spreadsheets and Student CD Package: International Edition
Autor Nagraj Balakrishnan, Barry Render, Ralph M. Stairen Limba Engleză Mixed media product – 30 iun 2006
This text emphasizes balancing the theory behind decision modeling and the use of spreadsheets to easily set up and solve these models. From a managerial perspective, the purpose of decision modeling is to gain insight into the problem, not the detailed mechanics of the solution process.
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Specificații
ISBN-13: 9780132446877
ISBN-10: 0132446871
Greutate: 1.18 kg
Ediția:2Nouă
Editura: Pearson Education
Colecția Pearson Education
Locul publicării:Upper Saddle River, United States
ISBN-10: 0132446871
Greutate: 1.18 kg
Ediția:2Nouă
Editura: Pearson Education
Colecția Pearson Education
Locul publicării:Upper Saddle River, United States
Cuprins
1. Introduction to Managerial Decision Modeling
2. Linear Programming Models: Graphical and Computer Methods
3. Linear Programming Modeling Applications with Computer Analyses in Excel
4. Linear Programming Sensitivity Analysis
5. Transportation, Assignment, and Network Models
6. Integer, Goal, and Nonlinear Programming Models
7. Project Management
8. Decision Analysis
9. Queuing Models
10. Simulation Modeling
11. Forecasting Models
12. Inventory Control Models
Appendix A Probability Concepts and Applications
Appendix B Useful Excel Commands and Procedures for Installing Excel Modules
Appendix C Areas Under the Standard Normal Curve
Appendix D Brief Solutions to All Odd-Numbered End-of-Chapter Problems
2. Linear Programming Models: Graphical and Computer Methods
3. Linear Programming Modeling Applications with Computer Analyses in Excel
4. Linear Programming Sensitivity Analysis
5. Transportation, Assignment, and Network Models
6. Integer, Goal, and Nonlinear Programming Models
7. Project Management
8. Decision Analysis
9. Queuing Models
10. Simulation Modeling
11. Forecasting Models
12. Inventory Control Models
Appendix A Probability Concepts and Applications
Appendix B Useful Excel Commands and Procedures for Installing Excel Modules
Appendix C Areas Under the Standard Normal Curve
Appendix D Brief Solutions to All Odd-Numbered End-of-Chapter Problems
Notă biografică
Nagraj (Raju) Balakrishnan is Professor and Graduate Coordinator in the Department of Management at Clemson University. He holds Bachelors and Masters degrees in Mechanical Engineering from the University of Madras (India) and the University of Kentucky respectively, and a Ph.D. in Management from Purdue University. He previously taught at Tulane University.
Dr. Balakrishnan teaches courses in spreadsheet-based Decision Modeling, Business Statistics, Production and Operations Management, and Project Management. He has won several awards for teaching excellence both at Clemson and at Tulane. At Clemson, these include the MBA Professor of the Year award and the College of Business Graduate Teaching Excellence award (twice). He has also taught in Tulane University’s Executive MBA program.
Dr. Balakrishnan’s current research focuses on production scheduling, capacity allocation models, and problems related to configurations of supply chains. His articles have been published in leading academic journals such as Decision Sciences,Production and Operations Management,European Journal of Operational Research, Naval Research Logistics, IIE Transactions, Networks, and Computers & Operations Research. He serves as a Senior Departmental Editor of Production and Operations Management, Online Editor for the Production and Operations Management Society, and is the recipient of several awards for his research publications including Best Paper awards from the Decision Sciences Institute and the Institute of Industrial Engineers, the Clemson Department of Management Award for Scholarly Achievement, and the Clemson Board of Trustees Award for Faculty Excellence.
Dr. Balakrishnan is very active in writing proposals and has authored or co-authored successful grant proposals totaling over $400,000 from the National Science Foundation and other funding agencies. Several of these have been in collaboration with faculty from the College of Engineering and Sciences at Clemson University.
Dr. Balakrishnan lives in Clemson, SC with his wife Meena, son Nitin, and daughter Nandita. He enjoys traveling and Indian light music, and is an avid racquetball player.
Dr. Balakrishnan teaches courses in spreadsheet-based Decision Modeling, Business Statistics, Production and Operations Management, and Project Management. He has won several awards for teaching excellence both at Clemson and at Tulane. At Clemson, these include the MBA Professor of the Year award and the College of Business Graduate Teaching Excellence award (twice). He has also taught in Tulane University’s Executive MBA program.
Dr. Balakrishnan’s current research focuses on production scheduling, capacity allocation models, and problems related to configurations of supply chains. His articles have been published in leading academic journals such as Decision Sciences,Production and Operations Management,European Journal of Operational Research, Naval Research Logistics, IIE Transactions, Networks, and Computers & Operations Research. He serves as a Senior Departmental Editor of Production and Operations Management, Online Editor for the Production and Operations Management Society, and is the recipient of several awards for his research publications including Best Paper awards from the Decision Sciences Institute and the Institute of Industrial Engineers, the Clemson Department of Management Award for Scholarly Achievement, and the Clemson Board of Trustees Award for Faculty Excellence.
Dr. Balakrishnan is very active in writing proposals and has authored or co-authored successful grant proposals totaling over $400,000 from the National Science Foundation and other funding agencies. Several of these have been in collaboration with faculty from the College of Engineering and Sciences at Clemson University.
Dr. Balakrishnan lives in Clemson, SC with his wife Meena, son Nitin, and daughter Nandita. He enjoys traveling and Indian light music, and is an avid racquetball player.
Textul de pe ultima copertă
Prentice Hall Decision Science has a long history of publishing market-defining, leading- edge textbooks. This proud tradition continues with this exciting new edition of Balakrishnan/Render/Stair’s Managerial Decision Modeling with Spreadsheets, 2nd Edition. In this spreadsheet modeling text the authors first discuss the algebraic model so that the student can understand the logic and rationale behind the decision model. The spreadsheet implementation then closely follows the algebraic model for ease of understanding.
Balakrishnan, Render and Stair continue to set the standard with:
- Increased Quantity and Range of End-of-Chapter Exercises and Problems — Many of these exercises and problems include multi-part questions, providing a richer pool of questions from which to select, and making them better suited to a computer-based solution environment.
- Inclusion of Several New Decision Models — Now includes coverage of new decision models such as make-buy problems and allocation problems (in Linear Programming), min-max and max-min problems (in Network Models), set covering problems (in Binary Integer Programming), and additive decomposition problems (in Forecasting).
- Expanded discussions in the following topical areas —Simulation, Regression, LP Formulation, Integer and Nonlinear Programming, and Utility Theory.
Bookstores: To order this text, please use this isbn 013-226806-X.
Please contact your PH Rep for more packaging information or visit us on the web at www.prenhall.com/decisionscience
Students: Additional resources to enhance your understanding of the text material may be found on the text website at www.prenhall.com/balakrishnan.
Caracteristici
This text emphasizes balancing the theory behind decision modeling and the use of spreadsheets to easily set up and solve these models.
Do you spend time in class teaching students how to effectively set-up models? Would it be helpful if a text used a consistent format and color to help drive good spreadsheet techniques?
Consistent format for creating effective Excel models for linear, integer, goal, and nonlinear programming problems. (Chapters 2 to 6)
This text is available for personalization in the PHCBR custom database program. Select only the chapters you require or supplement with recommended case studies all under one cover. CLICK HERE to go directly to the PHCBR book-build site or visit our product page for additional information at pearsoncustom.com/business.
Do you spend time in class teaching students how to effectively set-up models? Would it be helpful if a text used a consistent format and color to help drive good spreadsheet techniques?
Consistent format for creating effective Excel models for linear, integer, goal, and nonlinear programming problems. (Chapters 2 to 6)
- Each decision modeling technique is presented in a three step framework: 1.Formulation/problem setup, 2. model solution, and 3. interpretation of the results
- Functional use of color in the spreadsheets to clarify and illustrate good spreadsheet modeling. (Chapters 2 to 6)
- For each example in the text, the authors first discuss the algebraic model so students can understand the logic behind the problem's formulation. Then they show its spreadsheet implementation for ease of understanding.
- Numerous screen captures of Excel outputs with detailed callouts explaining the important entries are presented in all chapters.
- Includes a brief introduction to Excel as an appendix.
- Numerous end-of-chapter exercises that are rigorous and better suited to a computer based solution environment. Many of these exercises include multi-part questions, giving instructors a rich pool of questions from which they can select.
- The authors discuss using Excel's standard built-in commands, Excel add-ins (i.e., Premium Solver for Education, Crystal Ball, and Treeplan), and other software (i.e., Project Management) to give instructors the ability to teach topics both with or without the use of additional Excel add-ins or software.
- A trial version of Microsoft Project can be packaged with the text at no additional cost.
- Excel files for all examples discussed in the text
- Self Tests and Key Equations- allow students to test their knowledge
- Premium Solver for Education
- 140-day student version of Crystal Ball and TreePlan can be used to solve simulation and decision analysis models
- Excel Modules- this program solves problems and examples in the queuing (Ch.9), forecasting (Ch. 11), and inventory control (Ch.12) chapters.
- Chapter 12 (Inventory Control Models)
This text is available for personalization in the PHCBR custom database program. Select only the chapters you require or supplement with recommended case studies all under one cover. CLICK HERE to go directly to the PHCBR book-build site or visit our product page for additional information at pearsoncustom.com/business.
Caracteristici noi
New End-of-Chapter Exercises
- On average, over 40 end-of-chapter exercises per chapter. Many of these exercises include multi-part questions, giving instructors a rich pool of questions from which they can select.
- Many of the existing chapter examples and end-of-chapter exercises have been revised to make them more rigorous and better suited to a computer based solution environment.
- Now includes coverage of new decision models such as make-buy problems and allocation problems (in Linear Programming), min-max and max-min problems (in Network Models), set covering problems (in Binary Integer Programming), and additive decomposition problems (in Forecasting).
- Now includes additional chapter examples in revenue management, queuing, and project management. Continues to illustrate simulation in Excel with and without Crystal Ball. Discusses use of Excel's Scenario Manager to vary multiple decision parameters simultaneously (simulation without Crystal Ball).
- Now includes detailed discussion of using Excel's Data Analysis add-in to develop simple and multiple regression models. Includes coverage of statistical significance of the relationship, standard error of the estimate, confidence intervals, and multicollinearity.
- Now includes a detailed set of guidelines designed to answer the question, "How do I know my LP model is right?"
- Now includes a detailed set of guidelines designed to answer the question, "Should we include Integer Requirements in a model?"
- Now includes coverage of why NLP models are difficult to solve, local versus global optimal solutions, and ways to identify these solutions using Solver.
- Now includes discussion of the construction of utility curves, risk premiums, and exponential utility functions.
- Since this topic is often covered as part of an Operations Management course we moved its presentation to the CD. The chapter has been updated and include new end-of -chapter problems.