VBA for Modelers: Developing Decision Support Systems, 4th Edition Front Cover

VBA for Modelers: Developing Decision Support Systems, 4th Edition

  • Length: 720 pages
  • Edition: 4
  • Publisher:
  • Publication Date: 2011-08-26
  • ISBN-10: 1133190871
  • ISBN-13: 9781133190875
  • Sales Rank: #738924 (See Top 100 Books)
Description

Chris Albright’s VBA FOR MODELERS, 4TH EDITION is an essential tool for helping you learn to use Visual Basic for Applications (VBA) as a means to automate common spreadsheet tasks, as well as to create sophisticated management science applications. VBA is the programming language for Microsoft Office. VBA FOR MODELERS contains two parts. The first part teaches the essentials of VBA for Excel. The second part illustrates how a number of management science models can be automated with VBA. From a user’s standpoint, these applications hide the details of the management science techniques and instead present a simple user interface for inputs and results.

Table of Contents

Part I: VBA Fundamentals
Ch 1: Introduction to VBA Development in Excel
Ch 2: The Excel Object Model
Ch 3: The Visual Basic Editor
Ch 4: Recording Macros
Ch 5: Getting Started with VBA
Ch 6: Working with Ranges
Ch 7: Control Logic and Loops
Ch 8: Working with Other Excel Objects
Ch 9: Arrays
Ch 10: More on Variables and Subroutines
Ch 11: User Forms
Ch 12: Error Handling
Ch 13: Working with Files and Folders
Ch 14: Importing Data into Excel from a Database
Ch 15: Working with Pivot Tables and Tables
Ch 16: Working with Ribbons, Toolbars, and Menus
Ch 17: Automating Solver and Other Applications
Ch 18: User-Defined Types, Enumerations, Collections, and Classes

Part II: VBA Management Science Applications
Ch 19: Basic Ideas for Application Development with VBA
Ch 20: A Blending Application
Ch 21: A Product Mix Application
Ch 22: A Worker Scheduling Application
Ch 23: A Production-Planning Application
Ch 24: A Transportation Application
Ch 25: A Stock-Trading Simulation Application
Ch 26: A Capital Budgeting Application
Ch 27: A Regression Application
Ch 28: An Exponential Utility Application
Ch 29: A Queueing Simulation Application
Ch 30: An Option-Pricing Application
Ch 31: An Application for Finding Betas of Stocks
Ch 32: A Portfolio Optimization Application
Ch 33: A Data Envelopment Analysis Application

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