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Operations Research and Management Science Handbook
     

Operations Research and Management Science Handbook

by A. Ravi Ravindran
 

ISBN-10: 0849397219

ISBN-13: 9780849397219

Pub. Date: 12/07/2007

Publisher: Taylor & Francis

Operations Research (OR) began as an interdisciplinary activity to solve complex military problems during World War II. Utilizing principles from mathematics, engineering, business, computer science, economics, and statistics, OR has developed into a full fledged academic discipline with practical application in business, industry, government and military. Currently

Overview

Operations Research (OR) began as an interdisciplinary activity to solve complex military problems during World War II. Utilizing principles from mathematics, engineering, business, computer science, economics, and statistics, OR has developed into a full fledged academic discipline with practical application in business, industry, government and military. Currently regarded as a body of established mathematical models and methods essential to solving complicated management issues, OR provides quantitative analysis of problems from which managers can make objective decisions. Operations Research and Management Science (OR/MS) methodologies continue to flourish in numerous decision making fields.

Featuring a mix of international authors, Operations Research and Management Science Handbook combines OR/MS models, methods, and applications into one comprehensive, yet concise volume. The first resource to reach for when confronting OR/MS difficulties, this text -

  • Provides a single source guide in OR/MS

  • Bridges theory and practice
  • Covers all topics relevant to OR/MS
  • Offers a quick reference guide for students, researchers and practitioners
  • Contains unified and up-to-date coverage designed and edited with non-experts in mind
  • Discusses software availability for all OR/MS
    techniques
  • Includes contributions from a mix of domestic and international experts
  • The 26 chapters in the handbook are divided into two parts. Part I contains 14
    chapters that cover the fundamental OR/MS models and methods. Each chapter gives an overview of a particular OR/MS model, its solution methods and illustrates successful applications. Part II of the handbook contains 11
    chapters discussing the OR/MS applications in specific areas. They include airlines, e-commerce, energy systems, finance, military, production systems, project management, quality control, reliability, supply chain management and water resources. Part

    II ends with a chapter on the future of OR/MS applications.

    Product Details

    ISBN-13:
    9780849397219
    Publisher:
    Taylor & Francis
    Publication date:
    12/07/2007
    Series:
    Operations Research Series
    Edition description:
    New Edition
    Pages:
    898
    Product dimensions:
    7.20(w) x 10.10(h) x 2.00(d)

    Table of Contents

    I OR/MS Models and Methods
    Linear Programming, K. G. Murty
    Brief History of Algorithms for Solving Linear Equations, Linear
    Inequalities, and LPs
    Applicability of the LP Model: Classical Examples of
    Direct Applications
    LP Models Involving Transformations of Variables
    Intelligent Modeling Essential to Get Good Results, an Example from
    Container Shipping
    Planning Uses of LP Models
    Brief Introduction to Algorithms for Solving LP Models
    Software Systems Available for Solving LP Models
    Multiobjective LP Models
    Nonlinear Programming, T.B. Trafalis and R.C. Gilbert
    Introduction
    Unconstrained Optimization
    Constrained Optimization
    Conclusion
    Integer Programming, M. Weng
    Introduction
    Formulation of IP Models
    Branch and Bound Method
    Cutting Plane Method
    Other Solution Methods and Computer Solution
    Network Optimization, M.B. Yildirim
    Introduction
    Notation
    Minimum Cost Flow Problem
    Shortest Path Problem
    Maximum Flow Problem
    Assignment Problem
    Minimum Spanning Tree Problem
    Minimum Cost Multicommodity Flow Problem
    Conclusions
    Multiple Criteria Decision Making, A.S. M. Masud and A. R. Ravindran
    Some Definitions
    The Concept of “Best Solution”
    Criteria Normalization
    Computing Criteria Weights
    Multiple Criteria Methods for Finite
    Alternatives
    Multiple Criteria Mathematical Programming Problems
    Goal Programming
    Method of Global Criterion and Compromise Programming
    Interactive Methods
    MCDM Applications
    MCDM Software
    Further Readings
    Decision Analysis, C. M. Klein
    Introduction
    Terminology for Decision Analysis
    Decision Making under Risk
    Decision Making under Uncertainty
    Practical Decision Analysis
    Conclusions
    Resources
    Dynamic Programming, J. A. Ventura
    Introduction
    Deterministic Dynamic Programming Models
    Stochastic Dynamic Programming Models
    Conclusions
    Stochastic Processes, S. H. Xu
    Introduction
    Poisson Processes
    Discrete-Time Markov Chains
    Continuous-Time Markov Chains
    Renewal Theory
    Software Products Available for Solving
    Stochastic Models
    Queueing Theory, N. Gautam
    Introduction
    Queueing Theory Basics
    Single-Station and Single-Class Queues
    Single-Station and Multiclass Queues
    Multistation and Single-Class Queues
    Multistation and Multiclass Queues
    Concluding Remarks
    Inventory Control, F. Azadivar and A. Rangarajan
    Introduction
    Design of Inventory Systems
    Deterministic Inventory Systems
    Stochastic Inventory Systems
    Inventory Control at Multiple Locations
    Inventory Management in Practice
    Conclusions
    Current and Future Research
    Complexity and Large-Scale Networks, H. P. Thadakamalla, S. R.T. Kumara, and R. Albert
    Introduction
    Statistical Properties of Complex Networks
    Modeling of Complex Networks
    Why “Complex” Networks
    Optimization in Complex Networks
    Conclusions
    Simulation, C. M. Harmonosky
    Introduction
    Basics of Simulation
    Simulation Languages and Software
    Simulation Projects—The Bigger Picture
    Summary
    Metaheuristics for Discrete Optimization Problems, R.K. Kincaid
    Mathematical Framework for Single Solution Metaheuristics
    Network Location Problems
    Multistart Local Search
    Simulated Annealing
    Plain Vanilla Tabu Search
    Active Structural Acoustic Control (ASAC)
    Nature Reserve Site Selection
    Damper Placement in Flexible Truss Structures
    Reactive Tabu Search
    Discussion
    Robust Optimization, H. J. Greenberg and T. Morrison
    Introduction
    Classical Models
    Robust Optimization Models
    More Applications
    Summary
    II OR/MS Applications
    Project Management, A. B. Badiru
    Introduction
    Critical Path Method
    PERT Network Analysis
    Statistical Analysis of Project Duration
    Precedence Diagramming Method
    Software Tools for Project Management
    Conclusion
    Quality Control, Q. Feng and K. C. Kapur
    Introduction
    Quality Control and Product Life Cycle
    New Trends and Relationship to Six Sigma
    Statistical Process Control
    Process Capability Studies
    Advanced Control Charts
    16.7 Limitations of Acceptance Sampling
    16.8 Conclusions
    Reliability, L. M. Leemis
    Introduction
    Reliability in System Design
    Lifetime Distributions
    Parametric Models
    Parameter Estimation in Survival Analysis
    Nonparametric Methods
    Assessing Model Adequacy
    Summary
    Production Systems,
    B. L. Foote and K. G. Murty
    Production Planning Problem
    Demand Forecasting
    Models for Production Layout Design
    Scheduling of Production and Service Systems
    Energy Systems, C. R. Hudson and A. B. Badiru
    Introduction
    Definition of Energy
    Harnessing Natural Energy
    Mathematical Modeling of Energy Systems
    Linear Programming Model of Energy Resource Combination
    Integer Programming Model for Energy Investment Options
    Simulation and Optimization of Distributed Energy Systems
    Point-of-Use Energy Generation
    Modeling of CHP Systems
    Economic Optimization Methods
    Design of a Model for Optimization of CHP System Capacities
    Capacity Optimization
    Implementation of the Computer Model
    Other Scenarios
    Airline Optimization, J. L. Snowdon and G. Paleologo
    Introduction
    Schedule Planning
    Revenue Management
    Aircraft Load Planning
    Future Research Directions and Conclusions
    Financial Engineering, A. R. Heching and A. J. King
    Introduction
    Return
    Estimating an Asset’s Mean and Variance
    Diversification
    Efficient Frontier
    Utility Analysis
    Black–Litterman Asset Allocation Model
    Risk Management
    Options
    Valuing Options
    Dynamic Programming
    Pricing American Options Using Dynamic Programming
    Comparison of Monte Carlo Simulation and Dynamic Programming
    Multi-Period Asset Liability Management
    Conclusions
    Supply Chain Management, D. P. Warsing
    Introduction
    Managing Inventories in the Supply Chain
    Managing Transportation in the Supply Chain
    Managing Locations in the Supply Chain
    Managing Dyads in the Supply Chain
    Discussion and Conclusions
    E-Commerce, S. Sadagopan
    Introduction
    Evolution of E-Commerce
    OR/MS and E-Commerce
    OR Applications in E-Commerce
    Tools–Applications Matrix
    Way Forward
    Summary
    Water Resources, G.V. Loganathan
    Introduction
    Optimal Operating Policy for Reservoir Systems
    Water Distribution Systems Optimization
    Preferences in Choosing Domestic Plumbing Materials
    Stormwater Management
    Groundwater Management
    Summary
    Military Applications, J. D. Weir and M. U. Thomas
    Introduction
    Background on Military OR
    Current Military Applications of OR
    Concluding Remarks
    Future of OR/MS Applications: A Practitioner’s Perspective, P. Balasubramanian
    Past as a Guide to the Future
    Impact of the Internet
    Emerging Opportunities Index

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