Basic Business Analysis and Operations Research

1. Introduction to BASIC 1.1 Dialects of the BASIC Language 1.2 Assignment and non-Executable Statements 1.3 Variables, Arrays and Standard Functions 1.4 Input and Output 1.5 Loops, Conditional Statements and User Defined Functions 1.6 Structured BASIC 1.7 The Approach of this Book to BASIC Programs 1.8 References 1.9 Appendix2. Introduction to Business Operations Research 2.1 Introduction 2.2 Mathematical Modeling 2.3 Microcomputers and Business Operations Research 2.4 The Approach of this Book to Business Operations Research 2.5 References3. Index Numbers Essential Theory 3.1 Indices Based on Simple Relatives 3.2 Deflators 3.3 Employee's Reports 3.4 Composite Indices 3.5 Index Numbers in Perspective Problems Programs 3.1 SIMPREL: Index of Simple Relatives 3.2 DEFLATR: Indices with and without Deflator Series 3.4 INDICES: Calculates Laspeyres, Paasche and Ideal Indices4. Data Fitting Essential Theory 4.1 A Straight Line Fit to Data 4.2 The Learning Curve 4.3 Fitting a Piecewise Linear Function by Least Squares 4.4 Cost-Volume-Profit (CVP) Analysis Problems Programs 4.1 LINEFIT: Linear Regression on a Controlled Variable 4.2 LCURVE: Learning Curve Regression 4.3 PIECELN: Piecewise Linear Regression 4.4 CVP: Cost-Volume-Profit Analysis5. Critical Path Network Analysis Essential Theory 5.1 Introduction 5.2 The Construction of a Progressive Network 5.3 Earliest and Latest Start Analysis 5.4 Graphics Output 5.5 Discussion Problems Programs 5.1 PROGNET: Assigns Activities to the Nodes of a Progressive Network 5.2 CRITPAT: Earliest and Latest Start Analysis 5.3 NETWORK: Draws Activities, Network Logic, Times and Critical Path6. Linear Programming Essential Theory 6.1 A Solution by Complete Enumeration of the Vertices 6.2 The Simplex Method of Linear Programming 6.3 Mixed Inequality and Equality Constraints 6.4 Post-Optimal Analysis Problems Programs 6.1 VERTEX: Generates Basic Variable Sets for all Bases 6.2 ENUMER: Obtains Basic Variable Values for all Bases 6.3 SIMPLEX: LP for < = Constraints with non-Negative RHS 6.4 2PHASE: LP for Mixed Inequality and Equality Constraints with non-Negative RHS 6.5 SENSITY: LP as 2PHASE with Ranging of RHS and Ζ Coefficients7. Markov Chains Essential Theory 7.1 Introduction to Markov Chains 7.2 An Illustrative Example 7.3 Maintenance Policies 7.4 Maintain n Periods after the Machine Last Received Attention 7.5 Maintain the Machine after n Calendar Periods Problems Programs 7.2A MARKOV: Markov Chain Analysis for First Ν Periods 7.2B LONGRUN: As Markov with Steady State Vector if it Exists 7.4 SCHEDC1: Cost of Policies for Preventative Maintenance Class C1 7.5 SCHEDC2: Cost of Policies for Preventative Maintenance Class C2Index