Cutting Stock: Determine how to cut larger pieces of wood, steel, etc.Content: Chapter 1 Introduction to Quantitative AnalysisChapter 2 Probability Concepts and ApplicationsChapter 3 Decision AnalysisChapter 4 Regression ModelsChapter 5 ForecastingChapter 6 Inventory Control ModelsChapter 7 Linear Programming Models: Graphical and Computer MethodsChapter 8 Linear Programming ApplicationsChapter 9 Transportation, Assignment, and Network ModelsChapter 10 Integer Programming, Goal Programming, and Nonlinear ProgrammingChapter 11 Project ManagementChapter 12 Waiting Lines and Queuing Theory ModelsChapter 13 Simulation ModelingChapter 14 Markov AnalysisChapter 15 Statistical Quality Control Online Modules 1 Analytic Hierarchy Process Online Modules 2 Dynamic Programming Online Modules 3 Decision Theory and the Normal Distribution Online Modules 4 Game Theory Online Modules 5 Mathematical Tools: Determinants and Matrices Online Modules 6 Calculus-Based Optimization Online Modules 7 Linear Programming: The Simplex Method Online Modules 8 Transportation, Assignment, and Network Algorithms Citation previewįor these Global Editions, the editorial team at Pearson has collaborated with educators across the world to address a wide range of subjects and requirements, equipping students with the best possible learning tools.Process Selection - Decide which of several processes (with different speeds, costs, etc.) should be used to make a desired quantity of product in a certain amount of time, at minimum cost.Blending: Determine which raw materials from different sources to blend to produce a substance with certain desired qualities at minimum cost.Machine Allocation: Allocate production of a product to different machines, with different capacities, startup cost and operating cost, to meet production target at minimum cost.Product Mix: Determine how many products of each type to assemble from certain parts to maximize profits while not exceeding available parts inventory.Bond Portfolio Exact Matching: Allocate funds to bonds to maximize portfolio return while ensuring that periodic liabilities are met - with or without reinvestment.Bond Portfolio Management: Allocate funds to bonds to maximize return while ensuring that the portfolio duration equals the investment horizon for maturity - with known or computed durations.Portfolio Optimization - Sharpe Model (CAPM): Uses Excel's regression functions to calculate alphas and betas for stocks relative to a market index, then uses these to find an efficient portfolio.Stock Portfolio Management: Uses a VBA macro to optimize several scenarios for minimum risk at different target rates of return, then draws a graph of the efficient frontier.Portfolio Optimization - Markowitz Model: Allocate funds to stocks to minimize risk for a target rate of return - with known or computed variances and covariances.
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When you download and install a free trial of our enhanced Solvers for desktop Microsoft Excel, you'll find that more than ninety (90) small, but fully functional, example models are available for your use - covering conventional optimization, simulation and risk analysis, decision analysis (using decision trees), simulation optimization, stochastic optimization, and robust optimization. You can run all of these models with the basic Excel Solver. Here is a comprehensive list of example models that you will have access to once you login.
To learn more, sign up to view selected examples online by functional area or industry. Optimization is a tool with applications across many industries and functional areas.