An accelerated solution method for two-stage stochastic models in disaster management /
General Material Designation
[Book]
First Statement of Responsibility
Emilia Graß.
.PUBLICATION, DISTRIBUTION, ETC
Place of Publication, Distribution, etc.
Wiesbaden, Germany :
Name of Publisher, Distributor, etc.
Springer Spektrum,
Date of Publication, Distribution, etc.
2018.
PHYSICAL DESCRIPTION
Specific Material Designation and Extent of Item
1 online resource (xvii, 155 pages) :
Other Physical Details
illustrations (some color)
SERIES
Series Title
Mathematische Optimierung und Wirtschaftsmathematik -- Mathematical Optimization and Economathematics,
ISSN of Series
2523-7926
INTERNAL BIBLIOGRAPHIES/INDEXES NOTE
Text of Note
Includes bibliographical references.
CONTENTS NOTE
Text of Note
Intro; Summary; Contents; List of Figures; List of Tables; List of Abbreviations; List of Symbols; 1 Introduction; 2 Two-Stage Stochastic Programs for Pre-Positioning Problems in Disaster Management; 2.1 Disaster Management; 2.1.1 Introduction; 2.1.2 Challenges; 2.1.3 Scenario Definition in Disaster Management; 2.2 Quantitative Models in Disaster Management: A Literature Review; 2.2.1 Two-Stage Stochastic Programs; 2.2.2 Pre-Positioning of Relief Items; 2.3 The Rawls and Turnquist [2010] Model; 2.3.1 Problem Description and Mathematical Formulation; 2.3.2 Extensions
Text of Note
3 Solution Algorithms in Disaster Management3.1 Solution Methods in Disaster Management: A Literature Review; 3.1.1 Exact Methods; 3.1.2 Heuristics; 3.2 Two-Stage Stochastic Programming; 3.2.1 Introduction; 3.2.2 The L-Shaped Method; 3.3 The Accelerated L-Shaped Method; 3.3.1 The Basic Idea; 3.3.2 Assumptions; 3.3.3 Specialized Primal-Dual Interior-Point Method; 4 Numerical Experiments; 4.1 Realistic Large-Scale Case Study; 4.1.1 Data; 4.1.2 Technical Specifications; 4.1.3 Computational Results; 4.2 Case Study Based on a Hurricane Forecast; 4.2.1 Data; 4.2.2 Computational Results; 4.3 Outlook
Text of Note
5 ConclusionBibliography; A Appendix; A.1 The Recourse Function: An Example; A.2 Newton's Method for Systems of Non-Linear Equations; A.3 Interior-Point Method: Proof of Convergence; A.4 Matlab Code: L-Shaped Method with Multi-Optimality Cuts; A.5 Matlab Code: SIMP; A.6 Gurobi Log Files; A.6.1 Small-Scale Case Study; A.6.2 Medium-Scale Case Study; A.6.3 Large-Scale Case Study; A.6.4 Katrina Case Study
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SUMMARY OR ABSTRACT
Text of Note
Emilia Graß develops a solution method which can provide fast and near-optimal solutions to realistic large-scale two-stage stochastic problems in disaster management. The author proposes a specialized interior-point method to accelerate the standard L-shaped algorithm. She shows that the newly developed solution method solves two realistic large-scale case studies for the hurricane prone Gulf and Atlantic coast faster than the standard L-shaped method and a commercial solver. The accelerated solution method enables relief organizations to employ appropriate preparation measures even in the case of short-term disaster warnings. Contents Quantitative Optimization Models in Disaster Management: A Literature Review Solution Methods in Disaster Management: A Literature Review The Accelerated L-Shaped Method Case Study Design Numerical Experiments and Analysis Target Groups Scientist and students in the fields of operations research, optimization and numerical algorithms Practitioners working in charities and NGOs About the Author Emilia Graß holds a PhD from the Hamburg University of Technology, Germany. She is currently working as guest researcher on the project cyber security in healthcare at the Centre for Health Policy, Imperial College London, UK. Her scientific focus is on stochastic programming, solution methods, disaster management and healthcare.--
OTHER EDITION IN ANOTHER MEDIUM
Title
Accelerated solution method for two-stage stochastic models in disaster management.