Prentice Hall
Engineering
Browse available resources for Industrial Engineering:
- Select a resource
- Resources for Industrial Engineering Instructor Resource Center myPearsonStore
ISBN-10: 0131889230
ISBN-13: 9780131889231
Publisher: Prentice Hall
Copyright: 2007
Format: Cloth; 840 pp
Published: 04/04/2006
Suggested retail price: $155.00
Buy from myPearsonStore
For junior/senior undergraduate and first-year graduate courses in Operations Research in departments of Industrial Engineering, Business Administration, Statistics, Computer Science, and Mathematics.
Significantly revised, this text streamlines the coverage of the theory, applications, and computations of operations research. Numerical examples are effectively used to explain complex mathematical concepts. A separate chapter of fully analyzed applications aptly demonstrates the diverse use of OR. The popular commercial and tutorial software AMPL, Excel, Excel Solver, and Tora are used throughout the book to solve practical problems and to test theoretical concepts. New materials include Markov chains, TSP heuristics, new LP models, and a totally new simplex-based approach to LP sensitivity analysis.
• New organization of the book
— Chapter 2 is dedicated to the development of LP models with all references to sensitivity and post-optimal analysis moved to chapters 3 and 4.
— Chapter 3 offers a unique and straightforward presentation of LP sensitivity analysis.
— Chapter 4 deals with LP post-optimal analysis based exclusively on duality theory.
— The coverage of Markov chains is expanded into a full Chapter 17.
— New (Excel-based) heuristics for the traveling salesperson (TSP) include the nearest neighbor and the reversal algorithms
— Computer solutions are provided for each algorithm and all software implementations are deliberately compartmentalized to minimize disruptions in the book.
• Case analysis - New Chapter 24 presents 15 fully-developed real-life applications with summaries given in pertinent chapters to emphasize the practical applications of OR.
• Software implementations.
- AMPL, the widely-used commercial modeling language, is integrated throughout the book with examples from linear/nonlinear/integer programming and networks.
- Excel spreadsheet implementations include dynamic programming, traveling salesperson, inventory, AHP, Bayes’ probabilities, “electronic” statistical tables, queuing, simulation, Markov chains, and nonlinear programming.
- The use of Excel Solver is expanded in the areas of linear, network, integer, and nonlinear programming.
- TORA continues to play the key role of user-friendly tutorial software.
• Accompanying CD-ROM includes:
- AMPL student version and numerous fully-developed AMPL models.
- TORA, the updated and easy-to-use tutorial optimization system.
- General ready-to-use Excel spreadsheet templates.
- Numerous fully-developed Excel Solver models.
- Four supplemental chapters and two appendixes.
• Complete integration throughout of the powerful programming language AMPL – Uses numerous examples ranging from linear and network to integer and nonlinear programming.
– The syntax of AMPL is given and the content is cross-referenced within the examples in the book.
• Chapter-length coverage of linear program modeling (Ch. 2):
– Includes applications in the areas of urban renewal, finance, investment, production planning, blending, scheduling, and trim loss.
– Provides end-of-section problems that deal with topics ranging from water quality management and traffic control to warfare.
• Expanded treatment of Markov chains in a new Chapter 19.
• Approximately 50 end-of chapter mini-cases of real-life situations.
• More than 1000 total end-of-section problems.
• Chapter-opening study guides – Facilitates the understanding of the material and the effective use of the accompanying software.
• Extensive use of Excel spreadsheet implementations throughout – Includes interactive user input in some spreadsheets to promote a better understanding of the underlying techniques.
• Expanded use of Excel Solver throughout the book, particularly in the areas of linear, network, integer, and nonlinear programming.
• Compartmentalization of all computer-related material – Appears either in separate sections or as AMPL/Excel/Solver/TORA moment subsections to minimize disruptions in the main presentation in the book.
Chapter 1: What is Operations Research?
1.1 Operations Research Models
1.2 Solving the OR Model
1.3 Queueing and Simulation Models
1.4 Art of Modeling
1.5 More than Just Mathematics
1.6 Phases of an OR Study
1.7 About this Book
Problems
References
Chapter 2: Modeling with Linear Programming
2.1 Two-Variable LP Model
2.2 Graphical LP Solution
2.3 Selected LP Applications
2.4 Computer Solution with Solver and AMPL
Problems
References
Chapter 3: The Simplex Method and Sensitivity Analysis
3.1 LP Model in Equation Form
3.2 Transition from Graphical to Algebraic Solution
3.3 The Simplex Method
3.4 Artificial Starting Solution
3.5 Special Cases in the Simplex Method
3.6 Sensitivity Analysis
Problems
References
Chapter 4: Duality and Post-Optimal Analysis
4.1 Definition of the Dual Problem
4.2 Primal-Dual Relationships
4.3 Economic Interpretation of Duality
4.4 Additional Simplex Algorithms
4.5 Post-Optimal Analysis
Problems
References
Chapter 5: Transportation Model and its Variants
5.1 Definition of the Transportation Model
5.2 Nontraditional Transportation Models
5.3 The Transportation Algorithm
5.4 The Assignment Model
5.5 The Transshipment Model
Problems
References
Chapter 6: Network Models
6.1 Scope and Definition of Network Models
6.2 Minimal Spanning Tree Algorithm
6.3 Shortest-Route Problem
6.4 Maximal Flow Model
6.5 CPM and PERT
Problems
References
Chapter 7: Advanced Linear Programming
7.1 Simplex Method Fundamentals
7.2 Revised Simplex Method
7.3 Bounded Variables Algorithm
7.4 Duality
7.5 Parametric Linear Programming
Problems
References
Chapter 8: Goal Programming
8.1 A Goal Programming Formulation
8.2 Goal Programming Algorithms
Problems
References
Chapter 9: Integer Linear Programming
9.1 Illustrative Applications
9.2 Integer Programming Algorithms
9.3 Traveling Salesperson (TSP) Problem
Problems
References
Chapter 10: Deterministic Dynamic Programming
10.1 Recursive Nature of Computations in DP
10.2 Forward and Backward Recursion
10.3 Selected DP Applications
10.4 Problem of Dimensionality
Problems
References
Chapter 11: Deterministic Inventory Models
11.1 General Inventory Model
11.2 Role of Demand in the Development of Inventory Models
11.3 Static Economic-Order-Quantity (EOQ) Models
11.4 Dynamic EOQ Models
Problems
References
Chapter 12: Review of Basic Probability
12.1 Laws of Probability
12.2 Random Variables and Probability Distributions
12.3 Expectation of a Random Variable
12.4 Four Common Probability Distributions
12.5 Empirical Distributions
Problems
References
Chapter 13: Decision Analysis and Games
13.1 Decision Making under Certainty–Analytic Hierarchy Process (AHP)
13.2 Decision Making under Risk
13.3 Decision under Uncertainty
13.4 Game Theory
Problems
References
Chapter 14: Probabilistic Inventory Models
14.1 Continuous Review Models
14.2 Single-Period Models
14.3 Multiperiod Model
Problems
References
15.2 Elements of a Queuing Model
15.3 Role of Exponential Distribution
15.4 Pure Birth and Death Models (Relationship between the Exponential and Poisson Distributions)
15.5 Generalized Poisson Queuing Model
15.6 Specialized Poisson Queues
15.7 (M/G/1):(GD/Inf/Inf)–Pollaczek-Khintchine (P-K) Formula
Problems
References
Chapter 16: Simulation Modeling
16.1 Monte Carlo Simulation
16.2 Types of Simulation
16.3 Elements of Discrete-Event Simulation
16.4 Generation of Random Numbers
16.5 Mechanics of Discrete Simulation
16.6 Methods for Gathering Statistical Observations
16.7 Simulation Languages
Problems
References
Chapter 17: Markov Chains
17.1 Definition of a Markov Chain
17.2 Absolute and n-Step Transition Probabilities
17.3 Classification of the States in a Markov Chain
17.4Steady-State Probabilities and Mean Return Times of Ergodic Chains
17.5 First Passage Time
17.6 Analysis of Absorbing States
Problems
References
Chapter 18: Classical Optimization Theory
18.1 Unconstrained Problems
18.2 Constrained Problems
Problems
References
Chapter 19: Nonlinear Programming Algorithms
19.1 Unconstrained Algorithms
19.2 Constrained Algorithms
Problems
References
Appendix A: AMPL Modeling Language
A.1 Rudimentary AMPL Model
A.2 Components of AMPL Model
A.3 Mathematical Expressions and Computed Parameters
A.4 Subsets and Indexed Sets
A.5 Accessing External Files
A.6 Interactive Commands
A.7 Iterative and Conditional Execution of AMPL Commads
A.8 Sensitivity Analysis Using AMPL
Reference
Appendix B: Statistical Tables
Appendix C: Partial Answers to Selected Problems
Index
On the CD
Chapter 20: Additional Network and LP Algorithms
20.1 Minimim-Cost Capacitated Flow Problem
20.2 Decomposition Alogrithm
20.3 Karmarkar Interior-Point Method
Problems
References
Chapter 21: Forecasting Models
21.1 Moving Average Technique
21.2 Exponential Smoothing
21.3 Maximization of the Event of Achieving a Goal
Problems
References
Chapter 22: Probabilistic Dynamic Programming
22.1 A Game of Chance
22.2 Investment Problem
22.3 Maximization of the Event of Achieving a Goal
Problems
References
Chapter 23: Markovian Decision Process
23.1 Scope of the Markovian Decision Problem
23.2 Finite-Stage Dynamic Programming Model
23.3 Infinite-Stage Model
23.4 Linear Programming Solution
Problems
References
Chapter 24: Case Analysis
Case 1: Airline Fuel Allocation Using Optimum Tankering
Case 2: Optimization of Heart Valves Production
Case 3: Scheduling Appointments at Australian Tourist Commission Trade Events
Case 4: Saving Federal Travel Dollars
Case 5: Optimal Ship Routing and Personnel Assignments for Naval Recruitment in Thailand
Case 6: Allocation of Operating Room Time in Mount Sinai Hospital
Case 7: Optimizing Trailer Payloads at PFG Building Glass
Case 8: Optimization of Crosscutting and Log Allocation at Weyerhaeuser
Case 9: Layout Planning of a Computer Integrated Manufacturing (CIM) Facility
Case 10: Booking Limits in Hotel Reservations
Case 11: Casey’s Problem: Interpreting and Evaluating a New Test
Case 12: Ordering Golfers on the Final Day of Ryder Cup Matches
Case 13: Inventory Decisions in Dell’s Supply Chain
Case 14: Analysis of an Internal Transport System in a Manufacturing Plant
Case 15: Telephone Sales Manpower Planning at Qantas Airways
Appendix D: Review of Vectors and Matrices
D.1 Vectors
D.2 Matrices
D.3 Quadratic Forms
D.4 Convex and Concave Functions
Problems
References
Appendix E: Case Studies
Operations Research [CORE TEXTS] (Industrial Engineering)
Production and Operations Management [CORE TEXTS] (Industrial Engineering)
Operations Research [CORE TEXTS] (Decision Science)
Operations Research: An Introduction
Eighth Edition
Hamdy A. Taha
This eighth edition streamlines the presentation of text material, providing a balanced coverage of the theory, applications, and computations of operations research. Complex mathematical concepts are explained by means of carefully designed examples. Practical applications are presented using multitudes of examples, targeted problems, fully developed case analyses, and case studies, all borrowed from situations published in the literature. Computations are supported throughout the text both at the commercial level (using AMPL®, Solver, and Excel®) and at the tutorial level (using the popular and user-friendly TORA™).
New Text Material:
· Chapter 2 is dedicated entirely to formulating linear programming models, with new applications in urban renewal, currency arbitrage, investments, production planning, and blending. New end-of-section problems deal with topics ranging from water quality management and traffic control to warfare.
· Chapter 3 presents the general LP sensitivity analysis, including dual prices and reduced costs, as a direct extension of the simplex tableau computations.
· Chapter 4 is now dedicated to LP post-optimal analysis based on duality.
· A combined nearest neighbor-reversal heuristic (with generic Excel implementation) is presented for the traveling salesperson problem in Chapter 9.
· Markov chains treatment has been expanded into a new Chapter 17.
· The totally new Chapter 24 on the CD presents 15 fully developed real-life applications with summaries given in pertinent chapters. The analysis, which often cuts across more than one OR technique (e.g., heuristics and LP, or ILP and queuing), deals with the modeling, data collection, and computational aspects of solving the problem (CD-ROM only).
· The new Appendix E on the CD includes approximately 50 mini cases of real-life situations.
· More than 1000 end-of-section problem are included in the book.
· Each chapter starts with a guide that facilitates the understanding of the material and the effective use of the accompanying software.
· All computer-related material has been deliberately compartmentalized in subsections to minimize disruptions in the main presentation of the book.
New Software Implementations:
· AMPL, the widely-used commercial modeling language, is integrated throughout the book with examples from linear/nonlinear/integer programming and networks. The examples also demonstrate AMPL’s superior interactive capabilities for model experimentation.
· To facilitate learning the language, AMPL’s full syntax is given in Appendix A and cross-referenced in the book examples.
· Excel spreadsheet implementations include dynamic programming, traveling salesperson, inventory, AHP, Bayes’ probabilities, “electronic” statistical tables, queuing, simulation, Markov chains, and nonlinear programming. Interactive user input in some spreadsheets is designed to promote better understanding of the underlying techniques.
· The use of Excel Solver has been expanded, particularly in the areas of linear, network, integer, and nonlinear programming.
· TORA continues to play the key role of tutorial software.
On the CD-ROM
· AMPL language (student version) with numerous fully developed models.
· TORA, the updated and easy-to-use tutorial optimization system.
· Numerous fully-developed AMPL models.
· General ready-to-use Excel spreadsheet templates.
· Numerous fully-developed Excel Solver models.
· Four supplemental chapters and two appendixes.
Pearson Prentice Hall
Upper Saddle River, NJ 07458
www.prenhall.com
ISBN: 0-13-188923-0
Pearson Higher Education offers special pricing when you choose to package your text with other student resources. If you're interested in creating a cost-saving package for your students, contact your Pearson Higher Education representative for pricing and ordering information.
Pearson Higher Education offers special pricing when you choose to package your text with other student resources. If you're interested in creating a cost-saving package for your students contact your Pearson Higher Education representative.