Business analytics with management science models and methods /
Asllani, Arbenauthor.
Includes bibliographical references (pages 361-368) and index.
Machine generated contents note: ch. 1 Business Analytics with Management Science -- Chapter Objectives -- Prescriptive Analytics in Action: Success Stories -- Introduction -- Implementing Business Analytics -- Business Analytics Domain -- Challenges with Business Analytics -- Exploring Big Data with Prescriptive Analytics -- Wrap Up -- Review Questions -- Practice Problems -- ch. 2 Introduction to Linear Programming -- Chapter Objectives -- Prescriptive Analytics in Action: Chevron Optimizes Processing of Crude Oil -- Introduction -- LP Formulation -- Solving LP Models: A Graphical Approach -- Possible Outcome Solutions to LP Model -- Exploring Big Data with LP Models -- Wrap Up -- Review Questions -- Practice Problems -- ch. 3 Business Analytics with Linear Programming -- Chapter Objectives -- Prescriptive Analytics in Action: Nu-kote Minimizes Shipment Cost -- Introduction -- General Formulation of LP Models -- Formulating a Large LP Model --
Contents note continued: Solving Linear Programming Models with Excel -- Big Optimizations with Big Data -- Wrap Up -- Review Questions -- Practice Problems -- ch. 4 Business Analytics with Nonlinear Programming -- Chapter Objectives -- Prescriptive Analytics in Action: Netherlands Increases Protection from Flooding -- Introduction -- Challenges to NLP Models -- Example 1: World Class Furniture -- Example 2: Optimizing an Investment Portfolio -- Exploring Big Data with Nonlinear Programming -- Wrap Up -- Review Questions -- Practice Problems -- ch. 5 Business Analytics with Goal Programming -- Chapter Objectives -- Prescriptive Analytics in Action: Airbus Uses Multi-Objective Optimization Models -- Introduction -- GP Formulation -- Example 1: Rolls Bakery Revisited -- Solving GP Models with Solver -- Example 2: World Class Furniture -- Exploring Big Data with Goal Programming -- Wrap Up -- Review Questions -- Practice Problems --
Contents note continued: ch. 6 Business Analytics with Integer Programming -- Chapter Objectives -- Prescriptive Analytics in Action: Zara Uses Mixed IP Modeling -- Introduction -- Formulation and Graphical Solution of IP Models -- Types of Integer Programming Models -- Solving Integer LP Models with Solver -- Solving Nonlinear IP Models with Solver -- Solving Integer GP Models with Solver -- The Assignment Method -- The Knapsack Problem -- Exploring Big Data with Integer Programming -- Wrap Up -- Review Questions -- Practice Problems -- ch. 7 Business Analytics with Shipment Models -- Chapter Objectives -- Prescriptive Analytics in Action: Danaos Saves Time and Money with Shipment Models -- Introduction -- The Transportation Model -- The Transshipment Method -- Exploring Big Data with Shipment Models -- Wrap Up -- Review Questions -- Practice Problems -- ch. 8 Marketing Analytics with Linear Programming -- Chapter Objectives --
Contents note continued: Prescriptive Analytics in Action: Hewlett Packard Increases Profit with Marketing Optimization Models -- Introduction -- RFM Overview -- RFM Analysis with Excel -- Optimizing RFM-Based Marketing Campaigns -- LP Models with Single RFM Dimension -- Marketing Analytics and Big Data -- Wrap Up -- Review Questions -- Practice Problems -- ch. 9 Marketing Analytics with Multiple Goals -- Chapter Objectives -- Prescriptive Analytics in Action: First Tennessee Bank Improves Marketing Campaigns -- Introduction -- LP Models with Two RFM Dimensions -- LP Model with Three Dimensions -- A Goal Programming Model for RFM -- Exploring Big Data with RFM Analytics -- Wrap Up -- Review Questions -- Practice Problems -- ch. 10 Business Analytics with Simulation -- Chapter Objectives -- Prescriptive Analytics in Action: Blood Assurance Uses Simulation to Manage Platelet Inventory -- Introduction -- Basic Simulation Terminology -- Simulation Methodology --
Contents note continued: Simulation Methodology in Action -- Exploring Big Data with Simulation -- Wrap Up -- Review Questions -- Practice Problems -- Appendix A Excel Tools for the Management Scientist -- 1.Shortcut Keys -- 2.Sumif -- 3.Averageif -- 4.Countif -- 5.Iferror -- 6.Vlookup Or Hlookup -- 7.transpose -- 8.sumproduct -- 9.if -- 10.Pivot Table -- Appendix B A Brief Tour of Solver -- Setting Up Constraints and the Objective Function in Solver -- Selecting Solver Options.
Business intelligence.
Business planning.
Business
Commercial statistics.