Dynamics of Disasters—Key Concepts, Models, Algorithms, and - download pdf or read online

By Ilias S. Kotsireas, Anna Nagurney, Panos M. Pardalos

ISBN-10: 3319437070

ISBN-13: 9783319437071

ISBN-10: 3319437097

ISBN-13: 9783319437095

This quantity effects from the “Second overseas convention on Dynamics of mess ups” held in Kalamata, Greece, June 29-July 2, 2015. The convention lined specific issues concerned with traditional and man-made mess ups comparable to warfare, chemical spills, and wildfires. Papers during this quantity research the finer issues of failures through:

  • Critical infrastructure protection
  • Resiliency
  • Humanitarian logistic
  • Relief provide chains
  • Cooperative video game theory
  • Dynamical systems
  • Decision making less than threat and uncertainty
  • Spread of diseases
  • Contagion
  • Funding for catastrophe relief
  • Tools for emergency preparedness
  • Response, and hazard mitigation

Multi-disciplinary theories, instruments, suggestions and methodologies are associated with mess ups from mitigation and preparedness to reaction and restoration. The interdisciplinary method of difficulties in economics, optimization, executive, administration, enterprise, humanities, engineering, drugs, arithmetic, machine technological know-how, behavioral experiences, emergency prone, and environmental experiences will interact readers from a wide selection of fields and backgrounds.

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Extra info for Dynamics of Disasters—Key Concepts, Models, Algorithms, and Insights: Kalamata, Greece, June–July 2015

Sample text

Assign each characteristic to node i randomly; that is, draw a random number for each characteristic and decide whether the node carries the characteristic or not. Step 2. Consider node j that is closest to node i. Step 3. 2. 1. Pick three characteristics carried by node i randomly and assign these characteristics to node j. Assign the remaining six characteristics to node j randomly. 2. Assign all nine characteristics to node j randomly. Step 4. Set i WD j and go to Step 2. We consider different values for K and Tmax for each network, and as a result we obtain 48 instances.

2007) present a tabu search algorithm and a variable neighborhood search algorithm. , 2010). Although the recent literature mostly focuses on developing advanced algorithms that can find near-optimal solutions for the TOP, the aforementioned greedy heuristics are still attractive as they can find good solutions quickly; indeed, the greedy heuristics developed for the TOP are widely used as benchmarks in the studies that present metaheuristics for the TOP. We are inspired by the competitive performance of the greedy algorithms that can effectively solve the TOP and focus on developing a greedy heuristic for the SARP.

Nat. Hazards Earth Syst. Sci. : The Fukushima disaster and Japan’s nuclear plant vulnerability in comparative perspective. Environ. Sci. Technol. : Methodology for Assessing the Risks of Terrorism, Countering Urban Terrorism in Russia and the United States, pp. 207–222. : Management of Risks Associated with Mining Wasted (Tailing Dams and Waste Heaps), Optimisation of Disaster Forecasting and Prevention Measures in the Context of Human and Social Dynamics, pp. 130– 143. : Assessment of the site effect vulnerability within urban regions by data envelopment analysis: a case study in Iran.

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Dynamics of Disasters—Key Concepts, Models, Algorithms, and Insights: Kalamata, Greece, June–July 2015 by Ilias S. Kotsireas, Anna Nagurney, Panos M. Pardalos


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