A Novel Approach for Determining Shelter Location-Allocation in Humanitarian Relief Logistics

2021 ◽  
Vol 12 (2) ◽  
pp. 52-68
Author(s):  
Panchalee Praneetpholkrang ◽  
Sarunya Kanjanawattana
Keyword(s):  
Decision Making ◽  
Disaster Response ◽  
Large Scale ◽  
Solution Process ◽  
Decision Makers ◽  
Computational Time ◽  
Optimal Solutions ◽  
Location Allocation ◽  
Novel Approach ◽  
Artificial Neural Network Ann

This study proposes a methodology that integrates the epsilon constraint method (EC) and artificial neural network (ANN) to determine shelter location-allocation. Since shelter location-allocation is a critical part of disaster response stage, fast decision-making is very important. A multi-objective optimization model is formulated to simultaneously minimize total cost and minimize total evacuation time. The proposed model is solved by EC because it generates the optimal solutions without intervention of decision-makers during the solution process. However, EC requires intensive computational time, especially when dealing with large-scale data. Thus, ANN is combined with EC to facilitate prompt decision-making and address the complexity. Herein, ANN is supervised by the optimal solutions generated by EC. The applicability of the proposed methodology is demonstrated through a case study of shelter allocation in response to flooding in Surat Thani, Thailand. It is plausible to use this proposed methodology to improve disaster response for the benefit of victims and decision-makers.

Fuzzy multi-attribute group decision making to identify the order of establishing temporary logistics hubs during disaster response

2019 ◽  
Vol 9 (1) ◽  
pp. 2-21 ◽  
Author(s):  
Rajali Maharjan ◽  
Shinya Hanaoka
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Disaster Response ◽  
Group Decision ◽  
Decision Makers ◽  
Numerical Illustration ◽  
Content Type ◽  
Using Data ◽  
The Impact ◽  
Post Disaster

Purpose The purpose of this paper is to reveal the importance of the order of establishment of temporary logistics hubs (TLHs) when resources (mobile storage units used as TLHs) are limited and to present the development and implementation of a methodology that determines the order of establishment of TLHs to support post-disaster decision making. Design/methodology/approach It employed a decision support system that considers multiple decision makers and subjective attributes, while also addressing the impreciseness inherent in post-disaster decision making for ordering the establishment of TLHs. To do so, an optimization model was combined with a fuzzy multi-attribute group decision making approach. A numerical illustration was performed using data from the April 2015 Nepal Earthquake. Findings The results showed the location and order of establishment of TLHs, and demonstrated the impact of decision makers’ opinions on the overall ordering. Research limitations/implications The study does not discuss the uncertain nature of the location problem and the potential need for relocation of TLHs. Practical implications This methodology offers managerial insights for post-disaster decision making when resources are limited and their effective utilization is vital. The results highlight the importance of considering the opinions of multiple actors/decision makers to enable coordination and avoid complication between the growing numbers of humanitarian responders during disaster response. Originality/value This study introduces the concept of the order of establishment of TLHs and demonstrates its importance when resources are limited. It develops and implements a methodology determining the order of establishment of TLHs to support post-disaster decision making.

scholarly journals Towards a More General Understanding of the Algorithmic Utility of Recurrent Connections

2021 ◽  
Author(s):  
Brett W. Larsen ◽  
Shaul Druckmann
Keyword(s):  
Decision Making ◽  
Large Scale ◽  
Neural Circuits ◽  
Computation Time ◽  
Computational Time ◽  
Feedforward Networks ◽  
Population Activity ◽  
Artificial Neural ◽  
The Difference ◽  
Recurrent Connections

AbstractLateral and recurrent connections are ubiquitous in biological neural circuits. The strong computational abilities of feedforward networks have been extensively studied; on the other hand, while certain roles for lateral and recurrent connections in specific computations have been described, a more complete understanding of the role and advantages of recurrent computations that might explain their prevalence remains an important open challenge. Previous key studies by Minsky and later by Roelfsema argued that the sequential, parallel computations for which recurrent networks are well suited can be highly effective approaches to complex computational problems. Such “tag propagation” algorithms perform repeated, local propagation of information and were introduced in the context of detecting connectedness, a task that is challenging for feedforward networks. Here, we advance the understanding of the utility of lateral and recurrent computation by first performing a large-scale empirical study of neural architectures for the computation of connectedness to explore feedforward solutions more fully and establish robustly the importance of recurrent architectures. In addition, we highlight a tradeoff between computation time and performance and demonstrate hybrid feedforward/recurrent models that perform well even in the presence of varying computational time limitations. We then generalize tag propagation architectures to multiple, interacting propagating tags and demonstrate that these are efficient computational substrates for more general computations by introducing and solving an abstracted biologically inspired decision-making task. More generally, our work clarifies and expands the set of computational tasks that can be solved efficiently by recurrent computation, yielding hypotheses for structure in population activity that may be present in such tasks.Author SummaryLateral and recurrent connections are ubiquitous in biological neural circuits; intriguingly, this stands in contrast to the majority of current-day artificial neural network research which primarily uses feedforward architectures except in the context of temporal sequences. This raises the possibility that part of the difference in computational capabilities between real neural circuits and artificial neural networks is accounted for by the role of recurrent connections, and as a result a more detailed understanding of the computational role played by such connections is of great importance. Making effective comparisons between architectures is a subtle challenge, however, and in this paper we leverage the computational capabilities of large-scale machine learning to robustly explore how differences in architectures affect a network’s ability to learn a task. We first focus on the task of determining whether two pixels are connected in an image which has an elegant and efficient recurrent solution: propagate a connected label or tag along paths. Inspired by this solution, we show that it can be generalized in many ways, including propagating multiple tags at once and changing the computation performed on the result of the propagation. To illustrate these generalizations, we introduce an abstracted decision-making task related to foraging in which an animal must determine whether it can avoid predators in a random environment. Our results shed light on the set of computational tasks that can be solved efficiently by recurrent computation and how these solutions may appear in neural activity.

Health Impacts of Large-Scale Floods: Governmental Decision-Making and Resilience of the Citizens

2008 ◽  
Vol 23 (S2) ◽  
pp. s70-s73 ◽  
Author(s):  
Dick Q.P. Fundter ◽  
Bas Jonkman ◽  
Steve Beerman ◽  
Corsmas L.P.M. Goemans ◽  
Rosanna Briggs ◽  
...  
Keyword(s):  
Decision Making ◽  
Large Scale ◽  
Health Impact ◽  
Population Based ◽  
Chronic Illnesses ◽  
Decision Makers ◽  
Natural Resistance ◽  
First Year ◽  
The Public ◽  
Life Saving

AbstractDuring the 15th World Congress on Disaster and Emergency Medicine in Amsterdam, May 2007 (15WCDEM), a targeted agenda program (TAP) about the public health aspects of large-scale floods was organized. The main goal of the TAP was the establishment of an overview of issues that would help governmental decision-makers to develop policies to increase the resilience of the citizens during floods. During the meetings, it became clear that citizens have a natural resistance to evacuations. This results in death due to drowning and injuries. Recently, communication and education programs have been developed that may increase awareness that timely evacuation is important and can be life-saving. After a flood, health problems persist over prolonged periods, including increased death rates during the first year after a flood and a higher incidence of chronic illnesses that last for decades after the flood recedes. Population-based resilience (bottom-up) and governmental responsibility (top-down) must be combined to prepare regions for the health impact of evacuations and floods. More research data are needed to become better informed about the health impact and consequences of translocation of health infrastructures after evacuations. A better understanding of the consequences of floods will support governmental decision-making to mitigate the health impact. A top-10 priority action list was formulated.

scholarly journals Avoiding impacts on biodiversity through strengthening the first stage of the mitigation hierarchy

Oryx ◽  
2017 ◽  
Vol 52 (2) ◽  
pp. 316-324 ◽  
Author(s):  
Ben Phalan ◽  
Genevieve Hayes ◽  
Sharon Brooks ◽  
David Marsh ◽  
Pippa Howard ◽  
...  
Keyword(s):  
Decision Making ◽  
Ecosystem Services ◽  
Impact Assessment ◽  
Large Scale ◽  
Decision Makers ◽  
Technical Knowledge ◽  
Political Will ◽  
Building Capacity ◽  
Mitigation Hierarchy ◽  
Conservation Organizations

AbstractThe mitigation hierarchy is a decision-making framework designed to address impacts on biodiversity and ecosystem services through first seeking to avoid impacts wherever possible, then minimizing or restoring impacts, and finally by offsetting any unavoidable impacts. Avoiding impacts is seen by many as the most certain and effective way of managing harm to biodiversity, and its position as the first stage of the mitigation hierarchy indicates that it should be prioritized ahead of other stages. However, despite an abundance of legislative and voluntary requirements, there is often a failure to avoid impacts. We discuss reasons for this failure and outline some possible solutions. We highlight the key roles that can be played by conservation organizations in cultivating political will, holding decision makers accountable to the law, improving the processes of impact assessment and avoidance, building capacity, and providing technical knowledge. A renewed focus on impact avoidance as the foundation of the mitigation hierarchy could help to limit the impacts on biodiversity of large-scale developments in energy, infrastructure, agriculture and other sectors.

scholarly journals Profiles, Proxies, and Assumptions: Decentralized, Communications-Resilient Planning, Allocation, and Scheduling

2019 ◽  
Vol 33 ◽  
pp. 9504-9509
Author(s):  
Ugur Kuter ◽  
Brian Kettler ◽  
Katherine Guo ◽  
Martin Hofmann ◽  
Valerie Champagne ◽  
...  
Keyword(s):  
Subject Matter ◽  
Disaster Response ◽  
Large Scale ◽  
Subject Matter Expert ◽  
Decision Makers ◽  
Military Operations ◽  
Expert Review ◽  
Realistic Problem ◽  
The Cost ◽  
Distributed Decision

Degraded communications are expected in large-scale disaster response and military operations, which nevertheless require rapid, concerted actions by distributed decision makers, each with limited visibility into the changing situation and in charge of a limited set of resources. We describe LAPLATA, a novel architecture that addresses these challenges by separating mission planning from allocation/scheduling for scalability but at the cost of some negotiation. We describe formal algorithms that achieve near-optimal performance according to mission completion percentage and subject matter expert review: assumption-based planning and replanning, profileassisted cooperative allocation, and schedule negotiation. We validate our approach on a realistic problem specification and compare results against subject matter expert solutions.

Novel Stable Approach with Probability Distribution for Multi-Criteria Decision-Making Problems of Multi-Valued Neutrosophic Sets

2020 ◽  
Vol 19 (05) ◽  
pp. 1271-1292
Author(s):  
Xu Libo ◽  
Li Xingsen ◽  
Cui Honglei
Keyword(s):  
Decision Making ◽  
Probability Distribution ◽  
Dynamic Change ◽  
Distribution Functions ◽  
Transformation Operator ◽  
Decision Makers ◽  
Multi Criteria Decision Making ◽  
Neutrosophic Sets ◽  
Dependent Function ◽  
Novel Approach

In this paper, a novel approach and framework based on interval-dependent degree and probability distribution for multi-criteria decision-making problems with multi-valued neutrosophic sets (MVNSs) is proposed. First, a simplified dependent function and distribution function are given and integrated into a concise formula, which is called the interval-dependent function and contains interval computing and probability distribution information in an interval. Then a transformation operator is defined and it is shown how to convert MVNSs into an interval set. Subsequently, the interval-dependent function with the probability distribution of MVNSs is deduced. Finally, an example and comparative analysis are provided to verify the feasibility and effectiveness of the proposed method. In addition, uncertainty analysis, which reflects the dynamic change of the ranking result with decision-makers’ preferences, is performed by setting different distribution functions, which increases the reliability and accuracy of the proposed method.

scholarly journals A Framework for Evidence-Based Decision Making in Large-Scale Food Fortification Programs

2020 ◽  
Vol 4 (Supplement_2) ◽  
pp. 1802-1802
Author(s):  
Valerie Friesen ◽  
Mduduzi Mbuya ◽  
Lynnette Neufeld ◽  
Frank T Weiringa
Keyword(s):  
Decision Making ◽  
Large Scale ◽  
Program Design ◽  
Decision Makers ◽  
Evidence Based ◽  
Food Fortification ◽  
Impact Pathway ◽  
Gates Foundation ◽  
The Impact ◽  
Evidence Based Decision Making

Abstract Objectives The use of evidence on program performance and potential for impact for decision making in food fortification programs is limited and often done in isolation from other micronutrient interventions. We present a framework for fortification stakeholders responsible for making program recommendations and decisions to facilitate and document evidence-based decision making. Methods First, we reviewed the literature to define the key decision makers and decisions necessary for effective fortification program design and delivery, informed by a clear impact pathway. Then we classified decisions by domain, identified data sources and criteria for their assessment, and adapted the GRADE Evidence to Decision framework to summarize the results. Finally, we considered how the framework would apply to different country programs to test its utility. Results Policymakers, particularly government ministries, and the food producers themselves are the most important decision makers in a fortification program, while technical support agencies, donor agencies, and the research community play important roles in translating data and evidence into contextualized recommendations that meet the needs of different decision makers. The main fortification decision types were classified into five domains across the impact pathway: 1) program design (need, food vehicle(s)); 2) program delivery (compliance, quality, coverage); 3) program impact (nutrient intake and status); 4) overlapping micronutrient interventions and/or under-served populations; and 5) decisions to continue or stop programs. Important criteria for the assessment of each decision type included priority, benefits/risks, equity, acceptability, and feasibility among others. Country examples illustrated the importance of coordinating decision-making in the context of overlapping micronutrient interventions to ensure continued safety and impact over time. Conclusions This framework is a practical tool to enable evidence-based decision making by fortification stakeholders. Using evidence in a systematic and transparent way can enable more effective program design, delivery, and ultimately health impacts. Funding Sources Bill & Melinda Gates Foundation.

Decision-making model for the evaluation of industrialized housing systems in Ethiopia

2019 ◽  
Vol 27 (1) ◽  
pp. 296-320 ◽  
Author(s):  
Yidnekachew Tesmamma Daget ◽  
Hong Zhang
Keyword(s):  
Decision Making ◽  
Construction Industry ◽  
Large Scale ◽  
Cost Effective ◽  
Housing Development ◽  
Decision Makers ◽  
Content Type ◽  
Housing Systems ◽  
Decision Factors ◽  
Important Decision

Purpose The industrialized housing system (IHS) is regarded as an effective building philosophy based on off-site construction techniques to achieve rapid and cost-effective housing development. The purpose of this paper is to develop a multi-criteria decision-making support system (DMSS) model for the evaluation of housing systems to select the relevant decision factors and to identify the types and characteristics of suitable IHSs for application in a mass housing development. Design/methodology/approach A multi-criteria DMSS model with the analytical hierarchy process was designed. Based on the literature review and also the response of the ten experts’ interviews, 30 decision factors were identified for evaluation. In addition, 5 IHSs were considered as a case study for testing the model. Then, 30 professionals participated in a questionnaire survey conducted to evaluate the priority vector importance level of the decision factors and housing systems. Findings The result of the decision-making process showed that the top three decision factors are customer needs, supply chain and the construction industry. In addition, both precast concrete beam and slab blocks, as well as agro stone panels are identified as suitable housing systems. The systems have the characteristics of being lightweight, easy to produce and erect, and cost-effective, and they use local input resources and semi-skilled labor. The findings also revealed the potential and practicality of the model among multiple alternatives across multiple decision factors. Research limitations/implications The study has faced the limitations of available professionals and experts who have rich experience in the application of IHSs. In addition, there were few types of alternative IHSs and limited practice of IHSs implementation in large-scale housing construction. These challenges caused limitations to the relevant data collection. In order to address these challenges, all the available experts from the different sectors of the construction industry with the experience of IHSs construction are invited to participate and the available alternative IHSs in the market are selected for evaluation. Practical implications The rational evaluation method used to determine the important decision factors and the general characteristics of the suitable housing systems can help housing developers and decision makers in developing countries to make informed and effective decisions. Social implications The findings of the study help to address the challenge of lack of sufficient housing supply to the overwhelming housing demand that exists and identify the most important decision factors and suitable housing systems that can be applied for the rapid and decent large-scale housing developments at an affordable price. Originality/value This paper bridges the knowledge gaps that exist regarding the identification and evaluation of IHSs in Ethiopia. This study can help practitioners, housing developers, and decision makers to make informed and effective decisions regarding the evaluation and selection of IHSs.

scholarly journals A normative decision-making model for cyber security

2019 ◽  
Vol 27 (5) ◽  
pp. 636-646
Author(s):  
Andrew M’manga ◽  
Shamal Faily ◽  
John McAlaney ◽  
Chris Williams ◽  
Youki Kadobayashi ◽  
...  
Keyword(s):  
Decision Making ◽  
Situation Awareness ◽  
Cyber Security ◽  
Decision Makers ◽  
Proof Of Concept ◽  
Security Analysts ◽  
Content Type ◽  
Novel Approach ◽  
Risk Scenario ◽  
Decision Making Model

Purpose The purpose of this paper is to investigate security decision-making during risk and uncertain conditions and to propose a normative model capable of tracing the decision rationale. Design/methodology/approach The proposed risk rationalisation model is grounded in literature and studies on security analysts’ activities. The model design was inspired by established awareness models including the situation awareness and observe–orient–decide–act (OODA). Model validation was conducted using cognitive walkthroughs with security analysts. Findings The results indicate that the model may adequately be used to elicit the rationale or provide traceability for security decision-making. The results also illustrate how the model may be applied to facilitate design for security decision makers. Research limitations/implications The proof of concept is based on a hypothetical risk scenario. Further studies could investigate the model’s application in actual scenarios. Originality/value The paper proposes a novel approach to tracing the rationale behind security decision-making during risk and uncertain conditions. The research also illustrates techniques for adapting decision-making models to inform system design.

scholarly journals An Influence Network-Based Consensus Model for Large-Scale Group Decision Making with Linguistic Information

2022 ◽  
Vol 15 (1) ◽  
Author(s):  
Shengbao Yao ◽  
Miao Gu
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Large Scale ◽  
Group Decision ◽  
Decision Makers ◽  
Consensus Model ◽  
Group Consensus ◽  
Preference Information ◽  
Adjustment Strategy ◽  
Consensus Reaching

AbstractThe vast majority of the existing social network-based group decision-making models require extra information such as trust/distrust, influence and so on. However, in practical decision-making process, it is difficult to get additional information apart from opinions of decision makers. For large-scale group decision making (LSGDM) problem in which decision makers articulate their preferences in the form of comparative linguistic expressions, this paper proposes a consensus model based on an influence network which is inferred directly from preference information. First, a modified agglomerative hierarchical clustering algorithm is developed to detect subgroups in LSGDM problem with flexible linguistic information. Meanwhile, a measure method of group consensus level is proposed and the optimal clustering level can be determined. Second, according to the preference information of group members, influence network is constructed by determining intra-cluster and inter-cluster influence relationships. Third, a two-stage feedback mechanism guided by influence network is established for the consensus reaching process, which adopts cluster adjustment strategy and individual adjustment strategy depending on the different levels of group consensus. The proposed mechanism can not only effectively improve the efficiency of consensus reaching of LSGDM, but also take individual preference adjustment into account. Finally, the feasibility and effectiveness of the proposed method are verified by the case of intelligent environmental protection project location decision.

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