This extensively revised comprehensive textbook, covering a wide range of topics, is suitable for courses at the graduate and undergraduate levels, each with a different emphasis. There is more than enough material to cover two semesters of an undergraduate course, as well as a one semester graduate course. The pedagogy provides enough flexibility for an instructor to teach the topics in systems engineering she or he would like. Systems Engineering with Economics, Probability and Statistics,
Second Edition is sufficiently broad-based for undergraduate and graduate programs in various branches of engineering and management.

Key Features

Includes a wide range of topics covering the fundamentals and practice applications of probability and statistics (including advanced topics on statistical analysis, testing and interpretation of engineering data), microeconomics, engineering economics, hard systems (such as linear programming, decision analysis, CPM, LOB and PERT), soft systems analysis (such as Checkland’s method), and sustainable development and sustainability applications in engineering planning

Avoids the abstract mathematical approach usually found in textbooks on this subject, in favor of one that is geared to practical engineering applications

Integrates the power of quantitative analysis, in a very concrete way, with the conceptual richness of economics and systems thinking to deal with engineering problems

Examples and end-of-chapter exercises drives home the fact that answers to problems need not be merely “optimal” solutions, but must include value tradeoffs and lend themselves to an enriched decision-making process, most suitable for applications in an uncertain world. Numerous open-ended, real-world problems are included.

Includes a unique chapter on "systems thinking"—a first of its kind in a textbook on systems engineering. It covers the most recent soft systems structuring methods available in dealing with complexity, uncertainty, and conflict. A new case-studies chapter applying soft systems methods is also included.

Contains two new chapters—one on sustainable development, sustainability, engineering and planning; and the other on case studies dealing with engineering and planning for sustainability.

WAV material includes a solutions manual for those exercise problems that require numerical solutions — available from the Web Added Value™ Download Resource Center at www.jrosspub.com

About the Author(s)

Dr. C. Jotin Khisty is a Professor Emeritus of Civil and Architectural Engineering at the Illinois Institute of Technology (IIT), Chicago, Illinois. He was a professor of Civil Engineering and the Director of the Transportation and Infrastructure program at IIT from 1990 to 2002. Prior to joining IIT, he was on the faculty at Washington State University, Pullman, WA, from 1978 to 1990, where he also served as the Deputy Director of the Washington State Transportation Research Center. He gained his PhD in Transportation Systems Engineering from The Ohio State University, Columbus. He has had considerable field experience, first in India and Germany on large civil engineering projects, and later as a transportation engineer and planner with Metropolitan Planning Organizations in the USA. He has published more than 100 papers in journals, conference proceedings, and book chapters on systems science, transportation and traffic engineering, infrastructure systems planning, sustainable systems and economic analysis. He is the author of two books on transportation engineering. Dr. Khisty currently serves on the advisory committee of the International Journal of Systemic Practice and Action Research and on committees of the Transportation Research Board, National Academies, Washington, DC. He is a Life Member of the American Society of Civil Engineers, the Institute of Transportation Engineers, and the International Society of Systems Sciences. He is a registered professional engineer.

Dr. Jamshid Mohammadi is a professor of civil and architectural engineering at the Illinois Institute of Technology (IIT), Chicago, Illinois. Over the period 1997-2011, he also served as the chairman of the Department of Civil, Architectural and Environmental Engineering at IIT. He graduated from the University of Illinois at Urbana-Champaign with MS and PhD degrees. His publication records include more than 100 papers in journals and conference proceedings in the areas related to system reliability, probabilistic methods and risk analysis with specific applications in structural engineering. He is an author, co-author or editor of four books and conference proceedings. He served as the associate editor of Journal of Structural Engineering of the American Society of Civil Engineers (ASCE) from 1998-2004. Currently, he is the editor of ASCE’s Practice Periodical on Structural Design and Construction. He is a member of ASCE and has been active at ASCE in several committees including the fatigue and fracture reliability committee and structural reliability committee. He is a licensed professional engineer in Illinois, a registered civil engineer in California and a licensed structural engineer in Illinois.

Dr. Adjo Amekudzi is an associate professor of civil and environmental engineering at the Georgia Institute of Technology in Atlanta, Georgia. She earned her Bachelor’s degree in Civil Engineering (Structures) from Stanford University, Masters in Civil Engineering (Transportation) from Florida International University, and Masters in Civil Infrastructure Systems and Ph.D. in Civil and Environmental Engineering (Infrastructure Systems) from Carnegie Mellon University. Amekudzi’s research, teaching and professional activities focus on the study, development and application of systems methods to civil infrastructure decision making to promote sustainable development. She has published over fifty papers on sustainability planning and evaluation and infrastructure asset management, and an edited book on infrastructure reporting and asset management. Amekudzi is the founding chair of the Committee on Sustainability and the Environment of the Transportation and Development Institute of the American Society of Civil Engineers (ASCE). She serves on the Board on Infrastructure and the Constructed Environment (BICE) of the National Research Council of the National Academies. She is also on the editorial board of the International Journal of Sustainable Transportation, and as associate editor of the ASCE Journal of Transportation Engineering and ASCE Journal of Infrastructure Systems.

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