Practical Management Science - 5th Edition - by Wayne L. Winston, S. Christian Albright - ISBN 9781305250901

Practical Management Science
5th Edition
Wayne L. Winston, S. Christian Albright
Publisher: Cengage Learning
ISBN: 9781305250901

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Name: Practical Management Science
Author: Wayne L. Winston, S. Christian Albright
ISBN: 9781305250901

Chapter 2 - Introduction To Spreadsheet Modeling Chapter 2.4 - Breakeven Analysis Chapter 2.5 - Ordering With Quantity Discounts And Demand Uncertainty Chapter 2.6 - Estimating The Relationship Between Price And Demand Chapter 2.7 - Decisions Involving The Time Value Of Money Chapter 3 - Introduction To Optimization Modeling Chapter 3.6 - Infeasibility And Unboundedness Chapter 3.7 - A Larger Product Mix Model Chapter 3.8 - A Multiperiod Production Model Chapter 4 - Linear Programming Models

Chapter 4.2 - Advertising Models Chapter 4.3 - Employee Scheduling Models Chapter 4.4 - Aggregate Planning Models Chapter 4.5 - Blending Models Chapter 4.6 - Production Process Models Chapter 4.7 - Financial Models Chapter 4.8 - Data Envelopment Analysis (dea)Chapter 5 - Network Models Chapter 5.2 - Transportation Models Chapter 5.3 - Assignment Models Chapter 5.4 - Other Logistics Models Chapter 5.5 - Shortest Path Models Chapter 6 - Optimization Models With Integer Variables Chapter 6.3 - Capital Budgeting Models Chapter 6.4 - Fixed-cost Models Chapter 6.5 - Set-covering And Location-assignment Models Chapter 6.6 - Cutting Stock Models Chapter 7 - Nonlinear Optimization Models Chapter 7.3 - Pricing Models Chapter 7.4 - Advertising Response And Selection Models Chapter 7.5 - Facility Location Models Chapter 7.6 - Models For Rating Sports Teams Chapter 7.7 - Portfolio Optimization Models Chapter 7.8 - Estimating The Beta Of A Stock Chapter 8 - Evolutionary Solver: An Alternative Optimization Procedure Chapter 8.3 - Introduction To Evolutionary Solver Chapter 8.4 - Nonlinear Pricing Models Chapter 8.5 - Combinatorial Models Chapter 8.6 - Fitting An S-shaped Curve Chapter 8.7 - Portfolio Optimization Chapter 8.8 - Cluster Analysis Chapter 8.9 - Discriminant Analysis Chapter 8.10 - The Traveling Salesperson Problem Chapter 9 - Decision Making Under Uncertainty Chapter 9.2 - Elements Of Decision Analysis Chapter 9.3 - One-stage Decision Problems Chapter 9.4 - The Precision Tree Add-in Chapter 9.5 - Multistage Decision Problems Chapter 9.6 - The Role Of Risk Aversion Chapter 10 - Introduction To Simulation Modeling Chapter 10.2 - Probability Distributions For Input Variables Chapter 10.4 - Simulation With Built-in Excel Tools Chapter 10.5 - Introduction To @risk Chapter 10.6 - The Effects Of Input Distributions On Results Chapter 11 - Simulation Models Chapter 11.2 - Operations Models Chapter 11.3 - Financial Models Chapter 11.4 - Marketing Models Chapter 11.5 - Simulating Games Of Chance Chapter 12 - Inventory And Supply Chain Models Chapter 12.4 - Economic Order Quantity (eoq)Chapter 12.5 - Probabilistic Inventory Models Chapter 13 - Queueing Models Chapter 13.3 - The Exponential Distribution Chapter 13.4 - Important Queueing Relationships Chapter 13.5 - Analytic Steady-state Queueing Models Chapter 14 - Regression And Forecasting Models Chapter 14.3 - Simple Regression Models Chapter 14.4 - Multiple Regression Models Chapter 14.6 - Moving Averages Models Chapter 14.7 - Exponential Smoothing Models

Book Details

Geared entirely to Excel 2013, PRACTICAL MANAGEMENT SCIENCE uses an active-learning approach and realistic problems to help you take full advantage of the power of spreadsheet modeling. The text presents just the right amount of theory to ensure you understand the foundation of the topic, followed by exercises that give you practical, hands-on experience with the methodologies. Drawing examples and problems from finance, marketing, operations management, and other areas, the text illustrates how management science applies to your chosen profession--and how you can use it on the job. The authors emphasize modeling over algebraic formulations and memorization of particular models. The text includes access to Palisade DecisionTools Suite (BigPicture, @RISK, PrecisionTree, StatTools, TopRank, NeuralTools, and Evolver) as well as SolverTable, which allows you to do sensitivity analysis on optimization models.