Decision Support System (DSS) for Hierarchical Allocation of Resources and Tasks for Disaster Management

Jana, Shuvrangshu; Majumder, Rudrashis; Menon, Prathyush P.; Ghose, Debasish

doi:10.1007/s43069-022-00148-6

Cited by 5 publications

(3 citation statements)

References 55 publications

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“…DSS is now utilized in a variety of domains, and numerous studies have shown its use in multidisciplinary methodologies. It is utilized in e-commerce [7], disaster management [4], psychological therapy [5], drinking water systems [6], and the prediction of heart disease [8]. The use of DSS is expanding and getting better in the field of education [9, 10, 11, and [12].…”

Section: Decision Support System (Dss)mentioning

confidence: 99%

A Decision Support System for Predicting Students’ Performance in the National Achievement Test (NAT) of Senior High School Students

Casildo,

Aguirre,

Bonifacio

et al. 2023

Advances in Social Science, Education and Humanities Research

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Using data from the National Achievement Test (NAT) and student grades for senior high school students at Central Mindanao University, this study developed a Decision Support System (DSS). EDM, or educational data mining, must be completed prior to constructing the DSS. Support Vector Machine (SVM) with the Sigmoid kernel, the method used for EDM, achieved an overall accuracy of 96% with respect to the model. The model was then deployed in the DSS and saved. Leveraging Educational Data Mining and Machine Learning Techniques in Designing Strategic Interventions for Senior High School Students in CMU is a funded study that served as the basis for this study's inspiration.

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Section: Decision Support System (Dss)mentioning

confidence: 99%

A Decision Support System for Predicting Students’ Performance in the National Achievement Test (NAT) of Senior High School Students

Casildo,

Aguirre,

Bonifacio

et al. 2023

Advances in Social Science, Education and Humanities Research

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“…For example, task and resource allocation based on request from the aid centres assuming the data are available and reliable with no mention of the gap between the disaster strike and the data release [34]. They also are mostly based on the established distribution centres and fail to consider the ad hoc centres.…”

Section: Literature Reviewmentioning

confidence: 99%

A Multi-Attribute Decision Support System for Allocation of Humanitarian Cluster Resources Based on Decision Makers’ Perspective

Rye

Aktaş

2022

Sustainability

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The rush of the humanitarian suppliers into the disaster area proved to be counter-productive. To reduce this proliferation problem, the present research is designed to provide a technique for supplier ranking/selection in disaster response using the principles of utility theory. A resource allocation problem is solved using optimisation based on decision maker’s preferences. Due to the lack of real-time data in the first 72 h after the disaster strike, a Decision Support System (DSS) framework called EDIS is introduced to employ secondary historical data from disaster response in four humanitarian clusters (WASH: Water, Sanitation and Hygiene, Nutrition, Health, and Shelter) to estimate the demand of the affected population. A methodology based on multi-attribute decision-making (MADM), Analytical Hierarchy processing (AHP) and Multi-attribute utility theory (MAUT) provides the following results. First a need estimation technique is put forward to estimate minimum standard requirements for disaster response. Second, a method for optimization of the humanitarian partners selection is provided based on the resources they have available during the response phase. Third, an estimate of resource allocation is provided based on the preferences of the decision makers. This method does not require real-time data from the aftermath of the disasters and provides the need estimation, partner selection and resource allocation based on historical data before the MIRA report is released.

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“…In general terms, DSSs are capable of managing, controlling, monitoring, and executing operational procedures, either scheduled or in an emergency [9]. This type of system has already been developed for realistic cases in the political sector for addressing natural disasters [10], epidemic incidents [11], transportation of inflammable or other hazardous materials, etc. [12] and in the security sector for search and rescue missions [13], urgent air transportation of patients [14], supply missions [15], and other similar complex missions in several areas in case of emergency situations [16] (see Appendix A).…”

mentioning

confidence: 99%

Methodologies and Handling Techniques of Large-Scale Information in Decision Support Systems for Complex Missions

Tsavdaridis,

Papaodysseus,

Karadimas

et al. 2024

Applied Sciences

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Designing integrating systems for support, real-time monitoring, and executing of complex missions is challenging, since they often fail due to high levels of complexity and overwhelming volume of input data. Past attempts have resorted to “ad hoc” solutions, which face issues of being non-updatable, non-upgradable, and not applicable to similar missions, necessitating a complete redesign and reconstruction of the system. In the national defense and security sector, the impact of this reconstruction requirement leads to significant costs and delays. This study presents advanced methodologies for organizing large-scale datasets and handling complex operational procedures systematically, enhancing the capabilities of Decision Support Systems (DSSs). By introducing Complex Mission Support Systems (CMSSs), a novel SS sub-component, improved accuracy and effectiveness are achieved. The CMSS includes mission conceptualization, analysis, real-time monitoring, control dynamics, execution strategies, and simulations. These methods significantly aid engineers in developing DSSs that are highly user-friendly and operational, thanks to human-reasoning-centered design, increasing performance and efficiency. In summary, the systematic development of data cores that support complex processes creates an adaptable and adjustable framework in a wide range of diverse missions. This approach significantly enhances the overall sustainability and robustness of an integrated system.

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Decision Support System (DSS) for Hierarchical Allocation of Resources and Tasks for Disaster Management

Cited by 5 publications

References 55 publications

A Decision Support System for Predicting Students’ Performance in the National Achievement Test (NAT) of Senior High School Students

A Decision Support System for Predicting Students’ Performance in the National Achievement Test (NAT) of Senior High School Students

A Multi-Attribute Decision Support System for Allocation of Humanitarian Cluster Resources Based on Decision Makers’ Perspective

Methodologies and Handling Techniques of Large-Scale Information in Decision Support Systems for Complex Missions

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