Basic Business Analysis and Operations Research

BASIC Business Analysis and Operations Research discusses how the Beginners All-purpose Symbolic Instruction Code (BASIC) can be utilized in business analysis. The book is comprised of seven chapters that tackle various topics about BASIC and business analysis. Chapters 1 and 2 provide an overview of BASIC and Operations Research. Chapter 3 covers index numbers and provides an introduction to programming in structured BASIC. The book also presents programs for Data Fitting, and then describes how a simple program can be developed to include progressive complexity. The programs for a range of computational tasks are also presented. The book also tackles Markov chains in the context of policies for preventative maintenance. The text will be of great use to undergraduate students of management, computer, technology, and science.

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 Appendix

2. 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 References

3. 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 Indices

4. 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 Analysis

5. 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 Path

6. 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 Coefficients

7. 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 C2

Index