Network and discrete location : models, algorithms, and applications

Praise for the First Edition This book is refreshing to read since it takes an important topic... and presents it in a clear and concise manner by using examples that include visual presentations of the problem, solution methods, and results along with an explanation of the mathematical and procedur...

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Bibliographic Details
Main Author: Daskin, Mark S.
Format: eBook Book Publication
Language:English
Published: Hoboken, N.J Wiley 2013
John Wiley & Sons, Incorporated
Wiley-Blackwell
Edition:2
Subjects:
Industrial location
Industrial location > Mathematical models
Mathematical models
ISBN:0470905360, 9780470905364, 1118537017, 9781118536964, 1118536991, 1118537033, 9781118537015, 9781118537039, 9781118536995, 1118536967
Online Access:Get full text
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Table of Contents:
  • 6.6 Computational Results Using the Heuristic Algorithms and the Lagrangian Relaxation Algorithm -- 6.7 Another Interesting Property or It Still Ain't Necessarily So -- 6.8 Summary -- Exercises -- 7. Fixed Charge Facility Location Problems -- 7.1 Introduction -- 7.2 Uncapacitated Fixed Charge Facility Location Problems -- 7.2.1 Heuristic Construction Algorithms -- 7.2.2 Heuristic Improvement Algorithms -- 7.2.3 A Lagrangian Relaxation Approach -- 7.2.4 A Dual-Based Approach -- 7.3 Capacitated Fixed Charge Facility Location Problems -- 7.3.1 Lagrangian Relaxation Approaches -- 7.3.2 Bender's Decomposition -- 7.4 Summary -- Exercises -- 8. Extensions of Location Models -- 8.1 Introduction -- 8.2 Multiobjective Problems -- 8.3 Hierarchical Facility Location Models -- 8.3.1 Basic Notions of Hierarchical Facilities -- 8.3.2 Basic Median-Based Hierarchical Location Formulations -- 8.3.3 Coverage-Based Hierarchical Location Formulations -- 8.3.4 Extensions of Hierarchical Location Formulations -- 8.4 Models of Interacting Facilities -- 8.4.1 Flows Between Facilities -- 8.4.2 Facilities with Proximity Constraints -- 8.5 Multiproduct Flows and Production/Distribution Systems -- 8.6 Location/Routing Problems -- 8.7 Hub Location Problems -- 8.8 Dispersion Models and Models for the Location of Undesirable Facilities -- 8.8.1 Dispersion Models -- 8.8.2 A Maxisum Model for the Location of Undesirable Facilities -- 8.9 An Integrated Location-Inventory Model -- 8.9.1 A Multiobjective Location-Inventory/Covering Model -- 8.9.2 A Look at Aggregation Effects -- 8.10 Reliability and Facility Location Modeling -- 8.10.1 The Expected Failure Case -- 8.10.2 Modeling a Malevolent Attacker -- 8.11 Summary -- Exercises -- 9. Location Modeling in Perspective -- 9.1 Introduction -- 9.2 The Planning Process for Facility Location -- 9.2.1 Problem Definition -- 9.2.2 Analysis
  • Network and Discrete Location: Models, Algorithms, and Applications -- Contents -- Preface to the First and Second Editions -- Acknowledgments -- 1. Introduction to Location Theory and Models -- 1.1 Introduction -- 1.2 Key Questions Addressed by Location Models -- 1.3 Example Problem Descriptions -- 1.3.1 Ambulance Location -- 1.3.2 Siting Landfills for Hazardous Wastes -- 1.3.3 Summary -- 1.4 Key Dimensions of Location Problems and Models -- 1.4.1 Planar Versus Network Versus Discrete Location Models -- 1.4.2 Tree Problems Versus General Graph Problems -- 1.4.3 Distance Metrics -- 1.4.4 Number of Facilities to Locate -- 1.4.5 Static Versus Dynamic Location Problems -- 1.4.6 Deterministic Versus Probabilistic Models -- 1.4.7 Single- Versus Multiple-Product Models -- 1.4.8 Private Versus Public Sector Problems -- 1.4.9 Single- Versus Multiple-Objective Problems and Models -- 1.4.10 Elastic Versus Inelastic Demand -- 1.4.11 Capacitated Versus Uncapacitated Facilities -- 1.4.12 Nearest Facility Versus General Demand Allocation Models -- 1.4.13 Hierarchical Versus Single-Level Models -- 1.4.14 Desirable Versus Undesirable Facilities -- 1.5 ATaxonomy of Location Models -- 1.5.1 Typology of Location Models -- 1.5.2 A Simple Analytic Model -- 1.6 Summary -- Exercises -- 2. Review of Linear Programming -- 2.1 Introduction -- 2.2 The Canonical Form of a Linear Programming Problem -- 2.3 Constructing the Dual of an LP Problem -- 2.4 Complementary Slackness and the Relationships Between the Primal and the Dual Linear Programming Problems -- 2.5 Solving a Linear Programming Problem in Excel -- 2.6 The Transportation Problem -- 2.7 The Shortest Path Problem -- 2.7.1 The Shortest Path Problem in Excel -- 2.7.2 The Shortest Path Problem in AMPL -- 2.8 The Out-of-Kilter Flow Algorithm -- 2.9 Integer Programming Problems -- 2.10 Summary -- Exercises
  • 3. An Overview of Complexity Analysis -- 3.1 Introduction -- 3.2 Basic Concepts and Notation -- 3.3 Example Computation of an Algorithm's Complexity -- 3.4 The Classes P and NP (and NP-Hard and NP-Complete) -- 3.5 Summary -- Exercises -- 4. Covering Problems -- 4.1 Introduction and the Notion of Coverage -- 4.2 The Set Covering Model -- 4.3 Applications of the Set Covering Model -- 4.4 Variants of the Set Covering Location Model -- 4.5 The Maximum Covering Location Model -- 4.5.1 The Greedy Adding Algorithm: A Heuristic Algorithm for Solving the Maximum Covering Location Model -- 4.5.2 Lagrangian Relaxation: An Optimization-Based Heuristic Algorithm for Solving the Maximum Covering Location Model -- 4.5.3 Other Solution Approaches and Example Results -- 4.6 An Interesting Model Property or It Ain't Necessarily So -- 4.7 The Maximum Expected Covering Location Model -- 4.8 Summary -- Exercises -- 5. Center Problems -- 5.1 Introduction -- 5.2 Vertex P-Center Formulation -- 5.3 The Absolute 1- and 2-Center Problems on a Tree -- 5.3.1 Absolute 1-Center on an Unweighted Tree -- 5.3.2 Absolute 2-Centers on an Unweighted Tree -- 5.3.3 Absolute 1-Center on a Weighted Tree -- 5.4 The Unweighted Vertex P-Center Problem on a General Graph -- 5.5 The Unweighted Absolute P-Center Problem on a General Graph -- 5.5.1 Characteristics of the Solution to the Absolute P-Center Problem -- 5.5.2 An Algorithm for the Unweighted Absolute P-Center on a General Graph -- 5.6 Summary -- Exercises -- 6. Median Problems -- 6.1 Introduction -- 6.2 Formulation and Properties -- 6.3 1-Median Problem on a Tree -- 6.4 Heuristic Algorithms for the P-Median Problem -- 6.5 An Optimization-Based Lagrangian Algorithm for the P-Median Problem -- 6.5.1 Methodological Development -- 6.5.2 Numerical Example -- 6.5.3 Extensions and Enhancements to the Lagrangian Procedures
  • 9.2.3 Communication and Decision -- 9.2.4 Implementation -- 9.2.5 Caveats on the Planning Process -- 9.3 Summary -- Exercises -- References -- Index