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The purpose of this paper is to present a new method for evaluation of emergency plans for unconventional emergency events by using the soft fuzzy rough set theory and methodology.

In response to the problems of insufficient risk identification, incomplete and inaccurate data and different preference of decision makers, a new model for emergency plan evaluation is established by combining soft set theory with classical fuzzy rough set theory. Moreover, by combining the TOPSIS method with soft fuzzy rough set theory, the score value of the soft fuzzy lower and upper approximation is defined for the optimal object and the worst object. Finally, emergency plans are comprehensively evaluated according to the soft close degree of the soft fuzzy rough set theory.

This paper presents a new perspective on emergency management decision making in unconventional emergency events. Also, the paper provides an effective model for evaluating emergency plans for unconventional events.

The paper contributes to decision making in emergency management of unconventional emergency events. The model is useful for dealing with decision making with uncertain information.

Given the widespread lack of homogeneity, consistency and quality control in emergency planning, this paper sets out to offer some suggestions, guidelines and models for the processes of drawing up, testing, revising and utilising an emergency plan.

The paper considers some definitions of the term “standard” and discussing the utility of the concept with respect to emergency planning. The subsequent analysis is based on the application of logical and observational criteria to the process of systematically building a framework on which to base a planning standard.

The paper enumerates 18 principles that can be used to judge the quality of emergency plans. The principles are treated as basic criteria to be used when formulating a standard. Next, the paper reviews existing standards in civil protection, risk management, emergency preparedness and humanitarian relief. After a brief discussion of the consultative process used in preparing an instrument for measuring quality, the paper presents a draft standard for an emergency plan. This is broadly focused on the local authority level and on the generic, “all‐hazards” approach. Finally, the paper describes a category‐based methodology for applying the standard.

Standards may be viewed as unnecessarily restrictive and overly prescriptive. However, they can instead be regarded as a useful means of helping to guarantee the quality, content and relevance of plans.

The application of a standard to the emergency planning process will help to make plans more functional and relevant and will ensure that their content is adequate for the task of predisposing resources during emergencies. It will also guarantee compatibility between plans made for different purposes or jurisdictions.

As few model standards exist in emergency management and planning, this paper offers one of the first attempts to provide a set of generic, comprehensive guidelines for the process of creating, testing, using and revising plans.

This paper aims to demonstrate how to make emergency decision when decision makers face a complex and turbulent environment that needs quite different decision-making processes from conventional ones. Traditional decision techniques cannot meet the demands of today’s social stability and security.

The main work is to develop an instance-driven classifier for the emergency categories based upon three fuzzy measures: features for an instance, solution for the instance and effect evaluation of the outcome. First, the information collected from the past emergency events is encodes into a prototype model. Second, a three-dimensional space that describes the locations and mutual distance relationships of the emergency events in different emergency prototypes is formulated. Third, for any new emergency event to be classified, the nearest emergency prototype is identified in the three-dimensional space and is classified into that category.

An instance-driven classifier based on prototype theory helps decision makers to describe emergency concept more clearly. The maximizing deviation model is constructed to determine the optimal relative weights of features according to the characteristics of the new instance, such that every customized feature space maximizes the influence of features shared by members of the category. Comparisons and discusses of the proposed method with other existing methods are given.

To reduce the affection to economic development, more and more countries have recognized the importance of emergency response solutions as an indispensable activity. In a new emergency instance, it is very challengeable for a decision maker to form a rational and feasible humanitarian aids scheme under the time pressure. After selecting a most suitable prototype, decision makers can learn most relevant experience and lessons in the emergency profile database and generate plan for the new instance. The proposed approach is to effectively make full use of inhomogeneous information in different types of resources and optimize resource allocation.

The combination of instances can reflect different aspects of a prototype. This feature solves the problem of insufficient learning data, which is a significant characteristic of emergency decision-making. It can be seen as a customized classification mechanism, while the previous classifiers always assume key features of a category.

The aim of this paper is to propose an optimization method for determining the emergency action, in which the compatibility between emergency alternatives and the collaborative relationship between departments are considered.

The individual emergency cost and individual emergency effect of each emergency alternative are calculated. And the collaborative emergency cost and collaborative emergency effect associated with a pair of emergency alternatives are calculated. Then, a bi-objective programming model maximizing the total emergency effect and minimizing the total emergency cost is constructed. A novel nondominated sorting genetic algorithm II (NNSGA II) is designed to solve the constructed model, subsequently. Finally, an example is given to illustrate the use of the proposed method, and the performance of NNSGA II is evaluated through a simulation experiment.

This paper proposes an effective method to manage complex emergency events that requires the coordinations of multiple departments. Also, this paper provides a new algorithm to determine an appropriate emergency action that performs well in managing both the emergency cost and emergency effect.

The findings contribute to the current methods in the field of emergency management. The method is used for dealing with the individual information of emergency alternatives and the collaborative information associated with a pair of alternatives.

The purpose of this paper is to design a numerical model to calculate the individual evacuation time among secondary students based on Knowledge, Attitude and Practice (KAP), human characteristics and travel distances.

Validated KAP questionnaires were distributed among 290 respondents. The KAP level was obtained based on the assigned scores. During a fire drill, the individual evacuation time was calculated by using personal digital watch while the travel distances were recorded and measured. A linear numerical model was derived by using multiple linear regression to identify the significant variables and the coefficients.

The CVI, CVR and Cronbach’s α value (0.75, 0.59 and 0.7, respectively) which are greater than minimum accepted level proved the reliability and consistency of the instrument. The evacuation time prediction by the developed numerical model showed strong correlation with the actual time (R=0.95). The regression analysis found that 89 per cent proportion of variance in the evacuation time are determined by the predictors. Based on the linear equation, it found that the decrease in weight, knowledge level and walking speed while increase in BMI, flat and stair travel distances could increase evacuation time. From the six significant variables, weight, walking speed, flat and stair distances showed significant correlation in the model with p<0.001, while BMI and knowledge showed p<0.05. The integration with mobility factors expand the formula which applicable within dynamic fire scenario.

The involvement of examination students in the study is restricted by the Ministry of Education Malaysia to avoid interruption of learning session which limited the data representation.

Instead of using the traditional direct measurement of the evacuation time, the developed numerical model is an alternative convenient approach which could be used as one of the pre-assessment tool to identify the level of safety among students. The low cost and shorter time application of this model become one of the greatest advantages compared to other available approaches. The calculated individual evacuation time could be used directly to develop a better fire safety policy.

The purpose of this paper is to systematically review published literature for the research question “what issues are considered (and changes made) for vulnerable groups as part of the chemical, biological, radiological, nuclear or explosive (CBRNe) response for casualty collection, decontamination, triage and casualty clearing processes?”.

Seven-stage framework from the PRISMA statement for research question, eligibility (definition), search, identification of relevant papers from title and abstract, selection and retrieval of papers, appraisal and synthesis. Data sources: Medline, Embase, Cochrane Library, Web of Science, Scopus (Elsevier), Chemical Abstracts, Assia (Proquest), Sociological abstracts (Proquest), Cinahl, HMIC, Health business elite, PsycInfo (ebsco), PILOTS (Proquest) and supplemented by other search strategies (e.g. exploding reference lists). The included references were critically appraised using the mixed methods appraisal tool (MMAT).

Results: 1,855 papers were returned from the literature search, of which 221 were screened by abstract and 48 by full paper. In total, 11 papers were included for appraisal, of which three achieved a quality score of 50 per cent or over. The papers were categorised into three phases on CBRNe response; evacuation, triage and decontamination.

The limitations of the search process included the use of emerging exclusion criteria. This may have excluded research that would provide more information in some topic areas but it was felt necessary to set a high publication standard for inclusion to generate trustworthy results and recommendations. The MMAT appraisal tool has been validated for different study types and provided a useful categorisation approach for critical appraisal, albeit resulting in only three included studies. Future reviews could include papers published in a wider range of languages to include research from non-English sources.

These evidence-based results should be used by practitioners to review current operational policies for vulnerable people and plan future improvements. Evacuation accessibility can be described as characteristics for exit, route and obstacles. This takes a systems approach to consider how building planning and layout can have implications for safety critical but low frequency events. Decontamination recommendations include: at least one additional re-robe section per mass decontamination unit and adaptations to the decontamination plan including accessible equipment for non-ambulatory individuals; and additional (specialist) staff in the decontamination team (sign language, interpreters and physical therapists).

Although very little new medium/high quality research is available, the findings are summarised as considerations for building design (route choice and information), communication (including vision, hearing and language differences) and the composition of the response team. It is suggested that evidence-based practice from other care domains could be considered (patient movement and handling) for fire service and ambulance guidelines.

Every day, small and big incidents happen all over the world, and given the human, financial and spiritual damage they cause, proper planning should be sought to deal with them so they can be appropriately managed in times of crisis. This study aims to examine humanitarian supply chain models.

A new model is developed to pursue the necessary relations in an optimal way that will minimize human, financial and moral losses. In this developed model, in order to optimize the problem and minimize the amount of human and financial losses, the following subjects have been applied: magnitude of the areas in which an accident may occur as obtained by multiple attribute decision-making methods, the distances between relief centers, the number of available rescuers, the number of rescuers required and the risk level of each patient which is determined using previous data and machine learning (ML) algorithms.

For this purpose, a case study in the east of Tehran has been conducted. According to the results obtained from the algorithms, problem modeling and case study, the accuracy of the proposed model is evaluated very well.

Obtaining each injured person's priority using ML techniques and each area's importance or risk level, besides developing a bi-objective mathematical model and using multiple attribute decision-making methods, make this study unique among very few studies that concern ML in the humanitarian supply chain. Moreover, the findings validate the results and the model's functionality very well.

The aim of this study as to find out an approach for emergency program selection.

The authors have generated six aggregation operators (AOs), namely picture fuzzy Yager weighted average (PFYWA), picture fuzzy Yager ordered weighted average, picture fuzzy Yager hybrid weighted average, picture fuzzy Yager weighted geometric (PFYWG), picture fuzzy Yager ordered weighted geometric and picture fuzzy Yager hybrid weighted geometric aggregations operators.

First of all, the authors defined the score and accuracy function for picture fuzzy set (FS), and some fundamental operational laws for picture FS using the Yager aggregation operation. After that, using the developed operational laws, developed some AOs, namely PFYWA, picture fuzzy Yager ordered weighted average, picture fuzzy Yager hybrid weighted average, PFYWG, picture fuzzy Yager ordered weighted geometric and picture fuzzy Yager hybrid weighted geometric aggregations operators, have been proposed along with their desirable properties. A decision-making (DM) approach based on these operators has also been presented. An illustrative example has been given for demonstrating the approach. Finally, discussed the comparison of the proposed method with the other existing methods and write the conclusion of the article.

To find the best alternative for emergency program selection.

The purpose of this paper is to present a statistical analysis of research into emergency management (EM) using information systems (IS) for the period 2000-2016.

In this study, research trends in the area of EM using IS are analysed using various parameters, including trends on publications and citations, disciplinary distribution, journals, research institutions and regional cooperation. Through a keyword co-occurrence analysis, this study identifies the evolution of the main keywords in this area, and examines the changes and developments in the main focus of scholars in this period. The study also explores the main research orientations in the field by analysing and integrating the results of two cluster analyses conducted from keyword- and reference-based perspectives, respectively.

The area of EM using IS has received increased attention and interest by researchers and practitioners. It is suggested that more cooperation among research institutions is required to help facilitate the further development of the area. Six main research orientations are identified: namely Web 2.0-enabled research, geographic information technology (IT), IT-based research, the contextual use of IT, crisis collaboration research and mass media communication research, since the research area first became popular in 2006.

This study is the first to comprehensively map the landscape of EM by conducting a bibliometric analysis of the research using IS. The authors’ findings can help academics and emergency managers gain a comprehensive understanding of the research area, and guide scholars towards producing more effective findings.

Robot appraisement under various dimensions and directions is a crucial issue in real-time manufacturing scenario. Logistic robots are programable-independent movable devices capable of transporting stuffs in a logistic cycle. The purpose of this paper is to opt for the most economical robot under chains of criteria, which is always considered as a sizzling issue in an industrial domain.

The authors proposed a cluster approach, i.e. ratio analysis, reference point analysis and full mutification form, embedded type-2 fuzzy sets with weighted geometric aggregation operator (WGAO) to tackle the elected problem of industrial robot. The motive to use WGAO coupled with type-2 fuzzy sets is to effectively undertake the uncertainty associated with comprehensive information of professionals against defined dimensions. Furthermore, the cluster approach is used to carry out the comparative analysis for evaluating robust scores against candidate robot’s manufacturing firms, considering 59 crucial beneficial and non-beneficial dimensions. A case research study is carried out to demonstrate the validity of the proposed approach.

The most challenging task in real-time manufacturing scenario is robot selection for a particular industrial application. This problem has become more complex in recent years because of advanced features and facilities that are continuously being incorporated into the robots by different manufacturers. In the past decade, robots have been selected in accordance with cost criteria excluding other beneficial criteria, which results in declined product quality, customer’s expectation, ill productivity, higher deliver time, etc. The proposed research incorporates the aforesaid issues and provides the various important attributes needed to be considered for the optimum evaluation and selection of industrial robots.

The need for changes in the technological dimensions (speed, productivity, navigation, upgraded product demands, etc.) of robot was encountered as a hardship work for managers to take wise decision dealing with a wide range of availability of robot types and models with distinct features in the manufacturing firms. The presented work aids the managers in taking their decisions effectively while dealing with the aforesaid circumstances.

The proposed work suggests chains of dimensions (59 crucial beneficial and non-beneficial dimensions) that can be used by managers to measure the economic worth of robot to carry out logistic activities in updated manufacturing environment. The proposed work evolves as an effective cluster approach-embedded type-2 fuzzy sets with WGAO to assess manufacturing firms under availability of low information.