Systems Engineering with Economics, Probability and Statistics

Table of Contents

Chapter 1: MAPPING THE TERRAIN OF THE SYSTEMS APPROACH
1.1 Introduction
1.2 The Nature of Science
1.3 Engineering Planning, Design, and Management
1.4 The Systems Approach
1.5 Steps in Systems Analysis
1.6 Classification of Systems
1.7 Systems Characteristics
1.8 Systems Analysis and Decision Making
1.9 Models and Model-Building
Summary
References
Exercises

Chapter 2: PROBLEM SOLVING AND DESIGNING IN ENGINEERING AND PLANNING
2.1 Introduction
2.2 Problem Solving and Designing
2.3 Hierarchy: Problem-Space, Trees, and Semi-Lattices
2.4 Problem Solving Styles
2.5 Wicked Problems
2.6 Measurement and Scaling
2.6.1 Sources of Data
2.6.2 Measurement
2.6.3 Scales of Measurement
2.7 System Model Types and Model-Building
2.7.1 Model Types
2.7.2 Models Used in Planning and Engineering
2.8 Problem-Solving Through Group or Committee Action
Summary
References
Exercises

Chapter 3: BASIC ENGINEERING ECONOMICS AND EVALUATION
3.1 Introduction
3.2 Notations
3.3 Simple Interest
3.4 Compound Interest
3.5 Uniform Series of Payments
3.5.1 Compound Amount Factor (CAF) 
3.5.2 Sinking Fund Factor (SFF) 
3.5.3 Present Worth Factor (PWF) 
3.5.4 Capital Recovery Factor (CRF) 
3.6 Uniform Gradient Series
3.7 Discrete Compound Interest Factors
3.8 Uniform Continuous Cash Flow and Capitalized Cost
3.9 Evaluation
3.10 Feasibility Issues
3.11 Evaluation Issues
3.12 The Evaluation Process
3.13 Values, Goals, Objectives, Criteria, and Standards
3.14 Estimation of Costs, Impacts, and Performance Levels
3.14.1 Capital, Operating, and Maintenance Costs
3.14.2 User Costs
3.14.3 Impacts
3.14.4 Performance Levels
3.15 Evaluation of Alternatives
3.16 Economic and Financial Concepts
3.17 Analysis Techniques
3.17.1 Economic Evaluation Methods (Efficiency Analysis) 
3.17.2 Cost-Effectiveness Analysis
3.17.3 Multicriteria Evaluation Method
3.17.4 Benefit-Cost Analysis
3.17.5 The Willingness-To-Pay Concept
3.18 Depreciation and Taxes
3.19 Reporting Results
Summary
References
Exercises

Chapter 4: BASIC MICROECONOMICS FOR ENGINEERS AND PLANNERS
4.1 The Scope of Economics and Microeconomics
4.2 Some Basic Issues of Economics
4.3 Demand for Goods and Services
4.4 Demand, Supply, and Equilibrium
4.5 Sensitivity of Demand
4.6 Factors Affecting Elasticities
4.6.1 Income Elasticities
4.6.2 Price Elasticities
4.6.3 Elasticity and Total Revenue
4.6.4 Price Elasticity of Supply
4.7 Kraft Demand Model
4.8 Direct and Cross Elasticities
4.9 Consumer Surplus
4.10 Costs
4.10.1 Laws Related To Costs
4.10.2 Average Cost
4.10.3 Marginal Cost
4.11 Consumer Choice
Summary
References
Exercises

Chapter 5: PRINCIPLES OF PROBABILITY: PART I—REVIEW OF PROBABILITY THEORY 
5.1 Introduction
5.2 Events
5.2.1 Complementary Event
5.2.2 Combination of Events
5.2.3 Mutually Exclusive and Collectively Exhaustive Events
5.3 Probability
5.3.1 Probability of the Union of Events
5.3.2 Conditional Probability and Probability of Intersection of Events
5.3.3 Bayes’ Theorem
5.3.4 deMorgan’s Rule
5.3.5 Total Probability Theorem
Summary
References
Exercises

Chapter 6: PRINCIPLES OF PROBABILITY: PART II—RANDOM VARIABLES AND PROBABILITY DISTRIBUTIONS 
6.1 Random Variables
6.1.1 Discrete Random Variables
6.1.2 Continuous Random Variables
6.2 Probability Functions
6.2.1 Probability Mass Function and Cumulative Distribution Function
6.2.2 Probability Density and Distribution Functions
6.3 Describing Parameters of a Random Variable
6.3.1 Mathematical Expectation
6.3.2 Mean or Expected Value
6.3.3 The Variance and Standard Deviation
6.3.4 Median and Mode
6.3.5 Moments of a Random Variable
6.4 Several Useful Probability Functions
6.4.1 Normal (Gaussian) Probability Density Function
6.4.2. Rayleigh Probability Density Function
6.4.3 Logarithmic Normal Probability Density Function
6.4.4 The T-Distribution
6.4.5 Binomial Distribution Function
6.4.6 Poisson Distribution Function
6.4.7 Exponential Distribution Function
Summary
References
Exercises
Chapter 7: PRINCIPLES OF PROBABILITY: PART III —JOINT PROBABILITY FUNCTIONS AND CORRELATED VARIABLES 
7.1 Introduction
7.2 Joint Probability Functions
7.2.1 Joint Probability Mass Function
7.2.2 Joint Probability Density Function
7.3 Covariance and Correlation
7.3.1 Covariance
7.3.2 Correlation Coefficient
7.3.3 Bivariate Normal Distribution
7.4 Functions of A Single Random Variable
7.4.1 Discrete Random Variable Case
7.4.2 Continuous Random Variable Case
7.5 Functions of Multiple Random Variables
7.5.1 Special Case: Linear Functions of Independent Normal Random Variables
7.5.2 Special Case: The Product (or Quotient) of Independent Log-Normal Random Variables
7.6. Approximate Methods for Computing Mean, Variance and Probability
7.6.1 Simulation Method
7.6.2 Approximate First and Second Order Estimates for the Mean and Variance
Summary
References
Exercises
Chapter 8: PRINCIPLES OF STATISTICS: PART I—ESTIMATION OF STATISTICAL PARAMETERS AND TESTING VALIDITY OF DISTRIBUTION FUNCTIONS 
8.1 Introduction
8.2 Data Compression
8.2.1 Processing Data into Occurrence Frequencies
8.2.2 Processing Time-Dependent Data
8.3 Estimation of Mean and Variance
8.4 Confidence Intervals for Statistical Parameters 
8.4.1 Confidence Intervals for the Mean
8.4.2 One-Sided Confidence Limits
8.4.3 Determination of the Sample Size in an Experiment
8.4.4 Confidence Intervals for Other Statistical Parameters
8.4.5 Determination of Sample Size for Estimating Proportions
8.5 Estimation of Statistical Parameters Using the Method of Maximum Likelihood
8.6 Testing Data for a Desired Distribution Model
8.6.1 Branch-and-Leaves Method
8.6.2 Determination of the Shape of Distribution from Frequency-of-Occurrence Diagram
8.6.3 Probability-Scaled Plotting
8.6.4 Chi-Square Goodness-of-Fit Test for Testing Validity of a Distribution Model
8.6.5 Kolmogorov-Smirnov Test 
Summary
References
Exercises

Chapter 9: PRINCIPLES OF STATISTICS: PART II—HYPOTHESIS TESTING, ANALYSIS OF VARIANCE, REGRESSION, AND CORRELATION ANALYSIS 
9.1 Introduction
9.2 Hypotheses Testing
9.2.1 Hypothesis and Significance Testing of a Population Mean
9.2.2 Hypothesis Testing of a Proportion
9.3 Comparing Two Population Means
9.3.1 Testing of Equality of Two Variances
9.3.2 Comparing Mean Values from Independent Populations with Identical Variances (Pooled T) 
9.3.3 Comparing Means from Independent Populations with Unequal Variances
9.3.4 Comparing Means from Dependent Populations (Paired T) 
9.4 Analysis of Variance
9.4.1 One-Way Classification, Completely Random Design with Fixed Effect
9.4.2 Multiple Range Test
9.4.3 Random Effect
9.5 Distribution-Free Methods
9.5.1 Test of Location for a Given Sample Data
9.5.2 Wilcoxon Signed-Rank Test
9.5.3 Wilcoxon Signed-Rank Test for Paired Data
9.5.4 Wilcoxon Rank-Sum Test for Unmatched Data
9.5.5 Tests for Several Populations
9.6 Regression and Correlation Analysis
9.6.1 Simple Linear Regression Analysis
9.6.2 Correlation Coefficient
9.6.3 Strength of Linear Correlation
9.6.4 Multiple Linear Regression Analysis
9.6.5 Nonlinear Regression
9.6.6 Spearsman’s Rank Correlation Coefficient
Summary
References
Exercises
Chapter 10: BASIC HARD SYSTEMS ENGINEERING—PART I
10.1 Introduction: Hard Systems Analysis
10.2 Methods Based On Calculus
10.2.1 Production Function Characteristics
10.2.2 Relationship among Total, Marginal, and Average Cost Concepts and Elasticity
10.2.3 The Method of Lagrange Multipliers
10.3 Critical Path Method
10.3.1 Key Concepts
10.3.2 CPM Scheduling
10.3.3 The Time-Grid Diagram and Bar Charts
10.3.4 Resource Scheduling
10.3.5 Time-Cost Optimization
10.4 Program Evaluation and Review Technique and the Line-of-Balance Technique
10.4.1 Key Concepts of PERT (See Figure 10.2) 
10.4.2 The LOB Technique
10.4.3 Progress Charts and Buffers
10.4.4 Resource and LOB Schedule
10.5 Network Flow Analysis
10.5.1 Key Concepts
10.5.2 Minimum Spanning Tree
10.5.3 The Maximal Flow Problem
10.5.4 Shortest-Path or Minimum-Path Technique
10.6 Linear Programming
10.6.1 The Graphical Method
10.6.2 Simplex Algorithm
10.6.3 Marginal Value or Shadow Pricing
10.6.4 Primal and Dual Problem Formulation Characteristics and Interpretation
10.6.5 Solving Minimization Problems with Simplex
10.6.6 Interpretation of the Primal and Dual Models
Exercises

Chapter 11: BASIC HARD SYSTEMS ENGINEERING—PART II
11.1 Introduction
11.2 Forecasting
11.2.1 Regularity
11.2.2 Use of Time Series
11.3 Transportation and Assignment Problem 
11.3.1 Introduction
11.3.2 Northwest Corner Method
11.3.3 The Minimum-Cost Cell Method
11.3.4 The Penalty or “Vogel’s” Method
11.3.5 How Do We Determine An Optimum Solution? 
11.3.6 The Unbalanced and Other Transportation Problems
11.3.7 The Assignment Problem
11.4 Decision Analysis
11.4.1 Overview
11.4.2 Decision Making Under Conditions of Uncertainty
11.4.3 Decision Making Under Uncertainty with Probabilities
11.5 Queuing Models 
11.5.1 Introduction
11.5.2 Characteristics of Queuing Systems
11.5.3 Model 1 (D/D/1) Deterministic Queuing Model
11.5.4 Model 2 (M/D/1) 
11.5.5 Model 3 M/M/1
11.5.6 The Economics and Operating Characteristics of Queuing Discipline
11.5.7 Model 4 M/M/N
11.6 Simulation 
11.6.1 Introduction
11.6.2 Random Numbers
11.6.3 Simulations Using Known Probabilities
11.7 Markov Analysis
11.7.1 Characteristics of Markov Analysis
11.7.2 Special Transition Matrices
Exercises

Chapter 12: SYSTEMS THINKING
12.1 Introduction 
12.2 Systems Thinking 
12.2.1 The Nature of Systems
12.2.2 System of Systems Thinking
12.3 Hard Systems Thinking
12.3.1 Preamble
12.3.2 Systems Analysis
12.3.3 Systems Engineering
12.2.4 Operations Research
12.4 Soft Systems Thinking
12.4.1 Preamble
12.4.2 The Path from Optimization to Learning
12.4.3 Checkland’s SSM
12.4.4 Ackoff’s Interactive Planning 
12.4.5 Senge’s Fifth Discipline
12.4.6 Strategic Options Development and Analysis (SODA) 
12.5 Critical Systems Thinking
12.6 Multimodal Systems Thinking
12.7 Reflections and Summary
References
Exercises

Chapter 13: SYSTEMS THINKING: CASE STUDIES
13.1 Introducing the Case Studies
13.2 Case Study 1: Transportation Project Selection Using Robustness Analysis
13.2.1 Introduction
13.2.2 Background: Robustness and Debility
13.2.3 Road Construction using Robustness
13.2.4 Algorithm for Robustness
13.2.5 Discussion and Summary
13.3 Checkland’s Soft Systems Methodology (SSM) and Multimethodology Application to the Chicago Region
13.3.1 Background: Mixing and Matching
13.3.2 The Chicago Region Characteristics and Root Definitions
13.3.3 Multimodal Performance Indicators
13.3.4 Discussion and Summary
13.4 Case Study 3: Using SODA for the Chicago Transit Authority Study
13.4.1 Introduction
13.4.2 Background: Brown Line Rehabilitation Project
13.4.3 Soda Application
13.4.4 Findings
13.4.5 Summary: Goals and Expectations
13.4.6 Discussion and Summary
13.5 Case Study 4: Crisis Management Using SSM for Bhopal Gas Tragedy
13.5.1 Introduction
13.5.2 Crisis Management
13.5.3 The Bhopal Gas Tragedy
13.5.4 Application of SSM
13.5.4.1 Formulation of Root Definitions
13.5.4.2 Conceptual Models
13.5.4.3 Comparison of Conceptual Models and Root Definitions
13.5.5 Lessons Learned and Actions to be Taken
13.5.6 The Crisis Management Program
13.5.7 Discussion and Summary
13.6 Concluding Remarks
References

Chapter 14: SUSTAINABLE DEVELOPMENT, SUSTAINABILITY, ENGINEERING AND PLANNING
14.1 Introduction to Sustainable Development and Sustainability
14.1.1 Important Sustainability Issues for the Engineering Community
14.1.2 ASCE Code of Ethics and Sustainable Development
14.1.3 Sustainability and Systems Thinking
14.1.4 System Interconnections and Interdependencies
14.1.5 Strong versus Weak Sustainability
14.1.6 Shallow and Deep Ecology
14.2 Models of Sustainable Development and Sustainability
14.2.1 The Triple Bottom Line Framework
14.2.2 The IPAT Model
14.2.3 The Ecological Footprint Model
14.2.4 Triaxial Representation of Technological Sustainability
14.2.5 The Quality of Life/Natural Capital Model
14.2.6 The Sustainability Footprint
14.2.7 The True Sustainability Index
14.3 Planning and Designing for Sustainable Development and Sustainability
14.3.1 Planning and Project Development Methodologies for Sustainable Development and Sustainability
References
Exercises

Chapter 15: CASE STUDIES IN ENGINEERING AND PLANNING FOR SUSTAINABILITY
15.1 Introduction
15.2 The Interface Company’s Approach to Sustainability
15.2.1 Interface’s Seven-Front Approach to Sustainability
15.2.2 Measuring Progress toward Sustainability
15.2.2.1 Verification and Certification
15.2.3 Concluding Remarks: Interface, Inc.’s Journey to Sustainability
15.2 The New Zealand Transportation Strategy
15.2.1 Defining Sustainable Transportation
15.2.2 Defining a Vision, Objectives and Targets
15.2.3 A Multi-Sector Approach
15.2.4 Implementation: Turning Strategy into Action
15.2.5 Monitoring, Reporting and Review
15.2.6 Concluding Remarks: New Zealand’s Transportation Strategy
15.3 Sustainability Evaluation of Transportation Plan Alternatives Using Multiple Attribute Decision Making (MADM) Methodology
15.3.1 MADM Approach for Sustainability Evaluation of Plan Alternatives
15.3.2 Applying MADM and the Sustainability Diamond: Identifying Superior Plans
15.3.3. Concluding Remarks: Applying MADM and Visualization for Selecting Plan Alternatives
15.4 Conclusion
References
Exercises 

INDEX