An accelerated solution method for two-stage stochastic models in disaster management / Emilia Gra€.
Grass, Emilia, author.
2018
GB5005
Available Online

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Title An accelerated solution method for two-stage stochastic models in disaster management / Emilia Gra€.
Author Grass, Emilia, author.
ISBN 9783658240813 (electronic book)
3658240814 (electronic book)
9783658240806
3658240806
DOI https://doi.org/10.1007/978-3-658-24081-3
Published Wiesbaden, Germany : Springer Spektrum, 2018.
Language English
Description 1 online resource (xvii, 155 pages) : illustrations
Item Number 10.1007/978-3-658-24081-3 doi
Call Number GB5005
Dewey Decimal Classification 363.34072/7
Summary Emilia Gra€ 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 Gra€ 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.-- Provided by publisher.
Bibliography, etc. Note Includes bibliographical references.
Access Note Access limited to authorized users.
Source of Description Online resource; title from PDF title page (SpringerLink, viewed November 9, 2018).
Series Mathematische Optimierung und Wirtschaftsmathematik, 2523-7926
Available in Other Form Print version: 9783658240806
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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

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

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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