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Decision aid models for disaster management and emergencies
Vitoriano B., Montero J., Ruan D., Atlantis Publishing Corporation, Paris, France, 2013. 340 pp. Type: Book (978-9-491216-73-2)
Date Reviewed: Jan 17 2014

Disaster management is a topic of major importance for all human societies, but it is also a hot topic for research, since it essentially concerns extremely complex systems and rare events that most often require the processing and exploitation of huge amounts of information by interdisciplinary methodologies from mathematics and computer science.

This book belongs to a series of publications on computational intelligence systems. It is a collection of 14 chapters, essentially papers, written by different teams of authors from Spain, the US, Turkey, the UK, China, France, Cuba, Belgium, and Australia. The editors of the collection are Begoña Vitoriano and Javier Montero from the Complutense University of Madrid, and Da Ruan from the Belgian Nuclear Research Centre.

As the editors point out in their preface, disasters usually have an impact not only locally but also globally, and decisions have to be made before, during, and after the disaster at an international level, by different organizations that prioritize policies in divergent and often conflicting ways.

In general, although decision-making in disaster situations is not a new subject of research, the divergent problems encountered and new challenges posed by increasing complexity make the subject attractive for research. Furthermore, it seems that there is no universal formulation or global methodological framework for all issues involved in the process of disaster management. Therefore, the book is a welcome and essential contribution to this crucial and complicated area, with valuable information regarding the state of the art in the field and stimulating ideas for further research.

Apart from the first chapters, which provide general information and literature reviews, the more technical and focused chapters deal with problems originating from high uncertainty and imprecision. It is reasonable that the theory and applications of fuzzy models dominate as methodological approaches, given that fuzzy theory is certainly highly associated with, and efficient for, modeling the uncertainty involved in complex situations.

The book starts with an introduction to the whole volume, discussing the role of information in decision-making during humanitarian operations. This chapter provides an operational research perspective on disaster management. The stages of management and the levels of response (local, national, and international) are discussed, and examples related to humanitarian logistics, environmental prediction, and fleet management are provided. The editors also highlight the importance of collaboration and coordination of different parties, the incorporation of dynamic forecast in decision aid models, and the need for real-time analysis.

The second chapter is a survey of decision aid models and systems for humanitarian logistics. It provides the fundamental definitions of concepts related to disaster management, and presents an extended literature review, thematically categorized, along with a list of the most important decision aid systems developed so far.

Chapter 3 deals with problems related to uncertainty, a factor characterizing the occurrence and consequences of disaster. The chapter is a review of different approaches for dealing with humanitarian logistics. The methodologies reviewed are classified into larger categories, such as risk mapping, stochastic programming, robust optimization, simulation models, and fuzzy sets. The tables providing summaries of related literature are very helpful, especially for new researchers in the field.

The fourth chapter deals with disaster response and decisions and activities just before or just after the occurrence of a disaster. The paper presents fuzzy inference systems as appropriate for disaster response, describes their fundamental notions, and provides a literature review. A fuzzy inference system for spontaneous volunteer management is presented.

Chapter 5 is a literature review of research on security for container line supply chain operations. After a set of basic definitions, the authors present their research, first from a general perspective and then for different specific issues, criteria, and tools.

The remaining chapters are more technical and deal with more specific problems and methods, some of them containing technical details and mathematical formulations. Specifically, chapter 6 presents fuzzy risk analysis for hazard evaluation by linguistic values in natural language. Chapter 7 explores a generic risk assessment framework based on belief rules. In chapter 8, the authors discuss emergency management with fuzzy semantic diagnosis of disaster and rescue actions using descriptions expressed in natural language. Chapter 9 describes a method for constructing intervals from single values in fuzzy preference relations when experts face the problem of lack of knowledge. In chapter 10, descriptive fuzzy rule-based classification systems are proposed for classifying the severity of disaster consequences. Chapter 11 proposes a network model for planning humanitarian relief operations, which the authors evaluate using real data from an earthquake disaster. Chapter 12 discusses fuzzy cognitive maps and their hierarchical clustering for modeling travel behavior. Chapter 13 presents a hierarchical assessment framework for evaluating safety against fire and explosion hazards in container line supply chains. Finally, chapter 14 describes a human situation awareness support system for avoiding technological disasters based on fuzzy risk assessment.

Overall, the book is recommended for researchers, teachers, and practitioners in the fields of operation research, decision support, and computational intelligence who wish to learn about the state of the art and recent advances in disaster management.

Reviewer:  Lefteris Angelis Review #: CR141903 (1404-0263)
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