Group decision support for hazards planning and emergency management: A Group Analytic Network Process (GANP) approach

Levy, Jason; Taji, Kouichi

doi:10.1016/j.mcm.2007.03.001

Cited by 98 publications

(76 citation statements)

References 22 publications

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“…All of the relevant data are from the "Community Contact" emergency exercise organized by the Brandon Emergency Support Team (BSET), held on Wednesday, 21 June 2006, in Brandon, Manitoba (also see [25]). In this exercise, there are four key experts, including the Brandon Police Service (DM 1 ), the Brandon Fire Division (DM 2 ), the Western Manitoba Hazardous Materials Technical Team (DM 3 ) and the Brandon School Division (DM 4 ), as a GDM framework.…”

Section: Application In Chemical Spill Emergency Managementmentioning

confidence: 99%

“…Then, the final rank of the alternatives is obtained as in Table 12. In Table 12, we denote GANP the group analytic network process approach in [25]. The results in Table 12 shows that there exists a ranking difference of the alternatives by the different methods.…”

Section: Application In Chemical Spill Emergency Managementmentioning

confidence: 99%

“…Actually, by virtue of the optimization Model (3), Table 12 shows that the ranking result is different from those by the other methods. Furthermore, the difference between Min-Max and DBM is less than that between Min-Max and the method in [25]. In other words, construction of optimization models to determine the weights is more promising for offering a believable priority of the alternatives.…”

Section: Application In Chemical Spill Emergency Managementmentioning

confidence: 99%

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New Min-Max Approach to Optimal Choice of the Weights in Multi-Criteria Group Decision-Making Problems

2015

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In multi-criteria group decision-making (MCGDM), one of the most important problems is to determine the weights of criteria and experts. This paper intends to present two Min-Max models to optimize the point estimates of the weights. Since each expert generally possesses a uniform viewpoint on the importance (weighted value) of each criterion when he/she needs to rank the alternatives, the objective function in the first model is to minimize the maximum variation between the actual score vector and the ideal one for all the alternatives such that the optimal weights of criteria are consistent in ranking all the alternatives for the same expert. The second model is designed to optimize the weights of experts such that the obtained overall evaluation for each alternative can collect the perspectives of the experts as many as possible. Thus, the objective function in the second model is to minimize the maximum variation between the actual vector of evaluations and the ideal one for all the experts, such that the optimal weights can reduce the difference among the experts in evaluating the same alternative. For the constructed Min-Max models, another focus in this paper is on the development of an efficient algorithm for the optimal weights. Some applications are employed to show the significance of the models and algorithm. From the numerical results, it is clear that the developed Min-Max models more effectively solve the MCGDM problems including the ones with incomplete score matrices, compared with the methods available in the literature. Specifically, by the proposed method, (1) the evaluation uniformity of each expert on the same criteria is guaranteed; (2) The overall evaluation for each alternative can collect the judgements of the experts as many as possible; (3) The highest discrimination degree of the alternatives is obtained.Appl. Sci. 2015, 5 999

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Section: Application In Chemical Spill Emergency Managementmentioning

confidence: 99%

Section: Application In Chemical Spill Emergency Managementmentioning

confidence: 99%

Section: Application In Chemical Spill Emergency Managementmentioning

confidence: 99%

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New Min-Max Approach to Optimal Choice of the Weights in Multi-Criteria Group Decision-Making Problems

2015

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“…A well-known MCDM model that has been used in GDSS is Analytic Hierarchy Process (AHP) [26][27][28]. [18] used Group Analytic Network Process (GANP) to support hazard planning and emergency management under incomplete information. They showed that both AHP and GANP have great potential to be deployed in specified case involving a group of DMs.…”

Section: International Journal Of Digital Information and Wireless Comentioning

confidence: 99%

“…Table 2.4 describes some of the research carried out on GDSS using specific models. [18] used GANP to support hazard planning and emergency management under incomplete information. They showed that GANP have great potential for use in specified case involving a group of DMs.…”

Section: Gdss Related Workmentioning

confidence: 99%

Group Decision Support System Based on Enhanced Ahp for Tender Evaluation

Ahmad¹

2014

IJDIWC

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Application of model base in group decision making that makes up a Group Decision Support System (GDSS) is of paramount importance. Analytic Hierarchy Process (AHP) is the multi-criteria decision making (MCDM) that has been applied in GDSS. In order to be effectively used in GDSS, AHP needs to be customized so that it is more user friendly with ease of used features. In this paper, we propose an enhanced AHP model for GDSS tendering. The enhanced AHP method used is the Guided Ranked AHP (GRAHP). It is a technique where decision matrix tables are automatically filled in based on ranked data. However, the generated values in the decision matrix tables can still be altered by following the guidelines which in turn serve the purpose of improving the consistency of the decision matrix table. This process is transparent to Decision Makers because the degree of data inconsistency is visible. A prototype system based on tendering process has been developed to test the GRAHP model in terms of its applicability and robustness.

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Prioritizing emergency shelter areas using hybrid multi-criteria decision approach: A case study

Trivedi

Singh

2017

J. Multi-Crit. Decis. Anal.

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Every year, more than 400 natural disasters affect global population. Adopting a resilient approach strengthens communities to survive and recover well from destabilizing events. Disasters destroy or damage houses and infrastructure, which calls for arrangement of temporary establishments to provide immediate evacuation and shelter to affected population. These sites are vital for an effective relief and must be strategically planned. Communities living in disaster-prone areas should prepare themselves well in advance for any future catastrophic event. This study adopts a hybrid group decision support approach for emergency shelter site selection problem. Initially, relevant factors for locating potential sites are identified by reviewing extant literature and through consultation from a panel of disaster management experts. Next, fuzzy analytic hierarchy process theory and technique for order preference by similarity to ideal solution have been used to prioritize identified criteria and to evaluate potential locations for displacement sites. A case study of the recent Nepal earthquake has been used to illustrate the effectiveness of the proposed model. The model offers a resilience building approach to prepare communities for any future contingency by proposing and prioritizing a set of planned displacement sites. KEYWORDSAHP, emergency shelters, fuzzy sets, group decision support, humanitarian logistics, TOPSIS | INTRODUCTIONA disaster can be defined as "a sudden, calamitous event that seriously disrupts the functioning of a community or society and causes human, material, and economic or environmental losses that exceed the community's or society's ability to cope using its own resources" (IFRC, 2015). There has been a significant increase in the number of disasters over the past decade: from fewer than 50 disasters per year reported in 1950 to more than 400 disasters in 2010 (EM-DAT, 2015). In view of this environmental uncertainty, the need to foster resilience amongst communities has been an area of attention amongst researchers, practitioners, and policy makers. The resilience approach has found applications in various fields and disciplines, resulting in multiple definitions of the concept (Norris, Tracy, & Galea, 2009).According to disaster risk management literature, resilience refers to the capacity of a society to "bounce back," resist, cope, and recover quickly from the impacts of hazards (Bruneau et al., 2003;Klein, Nicholls, & Thomalla, 2003;Timmerman, 1981). It is determined by the capacity of a social system to improve risk-reduction measures and learn from past disasters (United Nations International Strategy for Disaster Reduction, 2007). Another crucial aspect of resilience that has not been emphasized much in contemporary disaster resilience conceptualization is focus on preparedness (Aldunce, Beilin, Handmer, & Howden, 2014). Social systems should have sufficient capacity to prepare in order to mitigate and minimize losses, suffering, and social disruption (Bruneau et al., 2003; Inte...

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Group decision support for hazards planning and emergency management: A Group Analytic Network Process (GANP) approach

Cited by 98 publications

References 22 publications

New Min-Max Approach to Optimal Choice of the Weights in Multi-Criteria Group Decision-Making Problems

New Min-Max Approach to Optimal Choice of the Weights in Multi-Criteria Group Decision-Making Problems

Group Decision Support System Based on Enhanced Ahp for Tender Evaluation

Prioritizing emergency shelter areas using hybrid multi-criteria decision approach: A case study

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