Decision Analysis Procedure Research Articles

Perananan Dan Penerapan Data Warehouse Sebagai Pendukung Sistem Akademik Pada UIN Sumatera Utara

A data warehouse is where information can be stored for a very large scope, and in a comprehensive manner. Academic divisions can utilize the data warehouse's ability to aggregate data, which makes it easier for them to provide information to support evaluation and decision analysis procedures. The problem was that in the scientific division, the information warehouse was not accessible and could not provide important reports of the instruction and assessment process. The design of the data warehouse provides strategic information such as the number of new students in each batch and student status. The purpose of this research is to overcome the obstacles in implementing data from various different sources into the data warehouse. The method used in this research is a qualitative method that provides breadth in exploring in-depth and contextual information. The result of this research is to facilitate the academic system of UIN-SU to serve important information aimed at the academic division to process historical data and present accurate information for evaluation and decision making.

Intuitionistic fuzzy gained and lost dominance score based on symmetric point criterion to prioritize zero-carbon measures for sustainable urban transportation

PurposeAchieving a zero-carbon city requires a long-term strategic perspective. The authors propose a decision-making model which would take into account the economic, environmental and social impacts for prioritizing the zero-carbon measures for sustainable urban transportation.Design/methodology/approachAn integrated intuitionistic fuzzy gained and lost dominance score (IF-GLDS) model is introduced based on intuitionistic fuzzy Yager weighted aggregation (IFYWA) operators and proposed weight-determining IF-SPC procedure. In addition, a weighting tool is presented to obtain the weights of decision experts. Further, the feasibility and efficacy of developed IF-SPC-GLDS model is implemented on a multi-criteria investment company selection problem under IFS context.FindingsThe results of the developed model, “introducing zero-emission zones” should be considered as the first measure to implement. The preference of this initiative offers sustainable transport in India to achieve a zero-carbon transport by having the greatest impact on the modal shift from cars to sustainable mobility modes with a lower operational and implementation cost as well as having greater public support. The developed model utilized can be relocated to other smart cities which aim to achieve a zero-carbon transport. Sensitivity and comparative analyses are discussed to reveal the robustness of obtained result. The outcomes show the feasibility of the developed methodology which yields second company as the suitable choice, when compared to and validated using the other MCDA methods from the literature, including TOPSIS, COPRAS, WASPAS and CoCoSo with intuitionistic fuzzy information.Originality/valueA new intuitionistic fuzzy symmetry point of criterion (IF-SPC) approach is presented to find weights of criteria under IFSs setting. Then, an IF-GLDS model is introduced using IFYWA operators to rank the options in the realistic multi-criteria decision analysis (MCDA) procedure. For this purpose, the IFYWA operators and their properties are developed to combine the IFNs. These operators can offer a flexible way to deal with the realistic MCDA problems with IFS context.

COPRAS method based on interval-valued hesitant Fermatean fuzzy sets and its application in selecting desalination technology

This paper firstly introduces the idea of interval-valued hesitant Fermatean fuzzy set (IVHFFS). It is one of the significant theoretical and practical features, which derive from the integration of hesitant Fermatean fuzzy set (HFFSs) and interval number. In this study, we firstly present the basic concept, various operations and distance measures of IVHFFSs. Then, based on the operations of IVHFFSs, some aggregation operators (AOs) are proposed for aggregating the interval-valued hesitant Fermatean fuzzy information. Furthermore, some elegant properties of these operators are discussed in detail. To show the applicability, we discuss a decision analysis process on IVHFFSs environment with the help of conventional complex proportional assessment (COPRAS) methodology. Finally, the selection process of desalination technology for treating the feed water is also taken to validate the developed decision analysis procedure on IVHFFSs. This paper considers various criteria and sub-criteria in the assessment procedure and determines the most significant criteria influencing the desalination technology selection process are technical, social, environment and economic criteria, with significance weights of 0.3972, 0.289, 0.1653 and 0.1486, respectively. The work concludes that the reverse osmosis (RO) is the suitable desalination technology under the considered criteria followed by electrodialysis (ED), and multiple-effect distillation (MED). Moreover, the sensitivity investigation and comparative study are presented to verify the robustness and stability of the proposed method. The findings of this study show that the proposed model can suggest more feasible performance while facing several input uncertainties and influencing factors.

Interval-valued fermatean fuzzy sets with multi-criteria weighted aggregated sum product assessment-based decision analysis framework.

Fermatean fuzzy set, a generalization of the fuzzy set, is a significant way to tackle the complex uncertain information that arises in decision-analysis procedure and thus can be employed on a wider range of applications. Due to the inadequacy in accessible data, it is hard for decision experts to exactly define the belongingness grade (BG) and non-belongingness grade (NG) by crisp values. In such a situation, interval BG and interval NG are good selections. Thus, the aim of the study is to develop the doctrine of interval-valued Fermatean fuzzy sets (IVFFSs) and their fundamental operations. Next, the score and accuracy functions are proposed for interval-valued Fermatean fuzzy numbers (IVFFNs). Two aggregation operators (AOs) are developed for aggregating the IVFFSs information and discussed some axioms. Further, a weighted aggregated sum product assessment method for IVFFSs using developed AOs is introduced to handle the uncertain multi-criteria decision analysis problems. A case study of e-waste recycling partner selection is also considered to elucidate the feasibility and efficacy of the introduced framework. Finally, sensitivity and comparative analyses are given to elucidate the reliability and robustness of the obtained results.

A GIS-Based Spatial Variations Analysis of Water Quality in Domestic Wells in The Buttala Area, Sri Lanka

Water quality can be identified as the main agent of human health. Different approaches and techniques can be used to analyze groundwater quality. Among them, Geographical Information Systems (GIS) is one of the approaches that can be utilized to analyze water quality levels in a spatial context and it provides more powerful tools that can be interpreted the spatial variation of the water quality parameters over the geographical space.Accordingly,the study was conducted to analyze spatial variations of the water quality in drinking wells in the Buttala Divisional Secretariat (DSD) which is an agricultural area in the dry zone.The methodological procedure is extremely important in this type of research thus, the spatial Multi-Criteria Decision Analysis (MCDA) procedure was used. Multi-criteria analysis has been widely applied to solve decision-making problems related to the environment, and natural resource management. In the study, Analytic Hierarchy Process (AHP) and MCDA integrated approach were used to visualize the spatial patterns of the water quality in the study area and to formulate the water quality index map.To generate the water quality index map, pH value, turbidity, electrical conductivity (EC), florid, and nitrate of 48 water samples were collected from the domestic well and tube wells from 10 Grama Niladari Divisions (GND) in Buttala DS.The ArcGIS 10.3 software was used for spatial analysis like Inverse Distance Weighting (IDW) and kriging.The results revealed that 11.2% of the water of the drinking wells in the study area has a good fitness level, while 68.7% of wells show a moderate quality level. Out of the total samples is shown that 18.5% of wells had a poor-quality level, and 1.2%was found to be very poor for drinking purposes. And also, 0.4 % of the area is unsuitablefordrinking.The study shows that geospatial techniques are more effective for studying the water quality in any area in an accurate decision support tool.

Native trees provide more benefits than exotic trees when ecosystem services are weighted in Santiago, Chile

Urban forests are conformed by a variable representation of native and exotic species. Because these species differ in the morpho-functional traits that possess, they may have a differential participation in the provision of ecosystem services in cities. Here, we compare ecosystem services inferred from morpho-functional traits of native and exotic tree species present in Santiago, Chile. Five traits associated with ecosystem services valuation (Vi) were scored (1 versus 0), and compared between native and exotic tree species, weighting those ecosystem services according to multi-criteria decision analysis procedure (MCDA). We found that native and exotic species did not have significant differences in the ecosystem services provided to urban dwellers (F = 1.2; P > 0.05); but these results were obtained when ecosystem services were not weighted according to their demand in Santiago. When weights were pondered, native species provided more ecosystem services than did exotic trees (F = 7.1; P < 0.008). Complementarily, we also found that the ecosystem services ranked for native and exotic species did not correlate with their spatial distribution (occupancy, Oi). These results highlight the need to use criteria based on ecosystem services to tree planting in Santiago, prioritizing native species because, in comparison to exotic ones, they provide more ecosystem services demanded city dwellers.

Model-based evaluation of management options in ornamental plant nurseries

Agricultural management decisions are usually made without perfect knowledge. Decision Analysis (DA) approaches translate available uncertain information on costs, benefits and risks involved in decisions into actionable management recommendations. We illustrate the use of DA procedures to inform decisions on disease management strategies in ornamental plant production. We worked with heather growers and other stakeholders in North Rhine-Westphalia, Germany, to model the impacts of changing disease management practices and to generate comprehensive forecasts of net returns. Through sensitivity analysis and Value of Information assessment we identified critical uncertainties regarding the feasibility of improved practices. Partial Farm Budgets for decision options ranged from a loss of more than 200,000 € to a gain of nearly 70,000 € per hectare and year. Findings suggest that reducing pesticide applications without additional monitoring may substantially increase production risks (chance of loss of 76%) and that intensified plant monitoring is likely to increase net benefits (chance of gain of 68%) by allowing earlier detection and more focused fungicide application. Our Decision Analysis approach facilitated ex-ante evaluation of innovative management strategies in heather production, and it holds promise for similar evaluations in other agricultural production systems.

Reinforcement Learning Aided Robot-Assisted Navigation: A Utility and RRT Two-Stage Approach

This work proposes a robot-assisted navigation approach based on user intent adjustment, in the context of robotic walkers. Walkers are prescribed to users with gait disorders so that they can support their body weight on the upper limbs, however, the manipulation of such devices can be cumbersome for some users. Common problems for the users are lack of dexterous upper limb control and visual impairments. These problems can render walkers’ users helpless, making them unable to operate these devices effectively and efficiently. We present a new approach to robot-assisted navigation using a utility decision and safety analysis procedure with user intent adjustments learned by reinforcement learning (RL) and supported on a rapidly-exploring random tree inspired algorithm. The proposed approach offers full control of the assistive platform to the user until obstacles are detected. In dangerous scenarios, corrections are computed in order that the assistive platform avoids collisions and follows social norms, effectively guiding the user through the environment while enforcing safer routes. The experimental validation was carried out in a virtual environment and in a real world scenario using a robotic walker built in our lab (ISR-AIWALKER). Experimental results have shown that the proposed approach provides a reliable solution to the robot-assisted navigation of a robotic walker, in particular the use of utility theory to evaluate candidate motions together with a RL model increases the safety of the user’s navigation.

Meeting User Needs for Sea Level Rise Information: A Decision Analysis Perspective

AbstractDespite widespread efforts to implement climate services, there is almost no literature that systematically analyzes users' needs. This paper addresses this gap by applying a decision analysis perspective to identify what kind of mean sea level rise (SLR) information is needed for local coastal adaptation decisions. We first characterize these decisions, then identify suitable decision analysis approaches and the sea level information required, and finally discuss if and how these information needs can be met given the state of the art of sea level science. We find that four types of information are needed: (i) probabilistic predictions for short‐term decisions when users are uncertainty tolerant; (ii) high‐end and low‐end SLR scenarios chosen for different levels of uncertainty tolerance; (iii) upper bounds of SLR for users with a low uncertainty tolerance; and (iv) learning scenarios derived from estimating what knowledge will plausibly emerge about SLR over time. Probabilistic predictions can only be attained for the near term (i.e., 2030–2050) before SLR significantly diverges between low and high emission scenarios, for locations for which modes of climate variability are well understood and the vertical land movement contribution to local sea levels is small. Meaningful SLR upper bounds cannot be defined unambiguously from a physical perspective. Low‐ to high‐end scenarios for different levels of uncertainty tolerance and learning scenarios can be produced, but this involves both expert and user judgments. The decision analysis procedure elaborated here can be applied to other types of climate information that are required for mitigation and adaptation purposes.

Application of a hybrid Delphi and aggregation–disaggregation procedure for group decision-making

A hybrid procedure for group multiple criteria decision analysis is introduced that consolidates a moderated Delphi process with an autonomous aggregation–disaggregation mechanism. The research is based on the assumption that both consolidated approaches can lead to synergistic effects when properly combined. The paper justifies the hybrid procedure by comparing the three approaches, and by assessing it with a preliminary case study that is based on several factors of a universal framework for the evaluation of group decision-making methods and systems. These factors address convergence of the decision-making process, conflict resolution and cognitive complexity. The paper aims to define the decision-making process completely and thoroughly, fully operationalize all steps of the hybrid procedure algorithmically and methodologically and provide an application of the procedure. The application shows that the process converges and imposes acceptable cognitive load on the decision-makers, which implies that the hybrid procedure is able to perform efficiently.

Rational preference and rationalizable choice

We study a decision maker characterized by two binary relations. The first reflects his judgments about well-being, his mental preferences. The second describes the decision maker’s choice behavior, his behavioral preferences. We propose axioms that describe a relation between these two preferences, so between mind and behavior, thus disentangling two different perspectives on preferences: a description of tastes (and attitudes) and a way to organize behavioral data. We obtain two representations: one in which mental preferences uniquely determine choice behavior, another for which mental preferences direct behavior but room remains for biases and framing effects. Our results also provide a foundation for a decision analysis procedure called robust ordinal regression and proposed by Greco et al. (Eur J Oper Res 191:416–436, 2008).

Flexible decision analysis procedures for optimizing the sustainability of ageing infrastructure under climate change

Currently, there is significant interest in ensuring the sustainability and serviceability of infrastructure systems in the context of climate change. Indeed, a large proportion of existing structures already are in an advanced state of deterioration, thus affecting the sustainability and usefulness of these structures, and highlighting the need for better planning and decision analysis tools. Such tools would benefit from improved models to predict the residual life of structures, to estimate benefits derived from infrastructures, to account for uncertainties associated with physical and financial processes, and to provide more flexibility in decision-making strategies. These concepts are investigated through application of a risk-based decision-making model for reinforced concrete bridge decks in Montreal to estimate the optimal timing for deck repairs. A probabilistic deterioration model is used to predict the residual life of concrete decks as a function of exposure to de-icing salts using historical data and predictions from climate change scenarios. Historical data are used to validate model assumptions by comparing predicted condition states to observations from periodic inspections, while the climate scenarios are used to evaluate the impact of climate change on deterioration rates assuming that current deck design and de-icing salt management strategies are not modified. In this instance, the optimal timing for the first major repair is influenced by the uncertainty involved with climate change predictions and the future availability of funds, while ensuring the safety of users and the required level of service. The proposed framework, based on a cost-benefit analysis, is applicable to any infrastructure project.

Assessment of flood susceptible areas using spatially explicit, probabilistic multi-criteria decision analysis

GIS-based multi-criteria decision analysis (MCDA) is increasingly used to support flood risk assessment. However, conventional GIS-MCDA methods fail to adequately represent spatial variability and are accompanied with considerable uncertainty. It is, thus, important to incorporate spatial variability and uncertainty into GIS-based decision analysis procedures. This research develops a spatially explicit, probabilistic GIS-MCDA approach for the delineation of potentially flood susceptible areas. The approach integrates the probabilistic and the local ordered weighted averaging (OWA) methods via Monte Carlo simulation, to take into account the uncertainty related to criteria weights, spatial heterogeneity of preferences and the risk attitude of the analyst. The approach is applied to a pilot study for the Gucheng County, central China, heavily affected by the hazardous 2012 flood. A GIS database of six geomorphological and hydrometeorological factors for the evaluation of susceptibility was created. Moreover, uncertainty and sensitivity analysis were performed to investigate the robustness of the model. The results indicate that the ensemble method improves the robustness of the model outcomes with respect to variation in criteria weights and identifies which criteria weights are most responsible for the variability of model outcomes. Therefore, the proposed approach is an improvement over the conventional deterministic method and can provides a more rational, objective and unbiased tool for flood susceptibility evaluation.

A multi-criteria decision analysis of management alternatives for anaerobically digested kraft pulp mill sludge

The Multi-Criteria Decision Analysis (MCDA) procedure was used to compare waste management options for kraft pulp mill sludge following its anaerobic digestion. Anaerobic digestion of sludge is advantageous because it produces biogas that may be used to generate electricity, heat and biofuels. However, adequate management of the digested sludge is essential. Landfill disposal is a non-sustainable waste management alternative. Kraft pulp mill digested sludge applied to land may pose risks to the environment and public health if the sludge has not been properly treated. This study is aimed to compare several recycling alternatives for anaerobically digested sludge from kraft pulp mills: land application, landfill disposal, composting, incineration, pyrolysis/gasification, and biofuel production by algae. The MCDA procedure considered nine criteria into three domains to compare digested sludge recycling alternatives in a kraft pulp mill: environmental (CO2 emission, exposure to pathogens, risk of pollution, material and energy recovery), economic (overall costs, value of products) and technical (maintenance and operation, feasibility of implementation). The most suitable management options for digested sludge from kraft pulp mills were found to be composting and incineration (when the latter was coupled with recycling ash to the cement industry). Landfill disposal was the worst option, presenting low performance in feasibility of implementation, risk of pollution, material and energy recovery.

Neotectonic control on drainage systems: GIS-based geomorphometric and morphotectonic assessment for Crete, Greece

Geomorphic indices can be used to examine the geomorphological and tectonic processes responsible for the development of the drainage basins. Such indices can be dependent on tectonics, erosional processes and other factors that control the morphology of the landforms. The inter-relationships between geomorphic indices can determine the influence of regional tectonic activity in the shape development of drainage basins. A Multi-Criteria Decision Analysis (MCDA) procedure has been used to perform an integrated cluster analysis that highlights information associated with the dominant regional tectonic activity. Factor Analysis (FA) and Analytical Hierarchy Process (AHP) were considered within that procedure, producing a representation of the distributed regional tectonic activity of the drainage basins studied. The study area is western Crete, located in the outer fore-arc of the Hellenic subduction zone, one of the world's most tectonically active regions. The results indicate that in the landscape evolution of the study area (especially the western basins) tectonic controls dominate over lithological controls.

Demonstration of a modelling-based multi-criteria decision analysis procedure for prioritisation of occupational risks from manufactured nanomaterials

Several tools to facilitate the risk assessment and management of manufactured nanomaterials (MN) have been developed. Most of them require input data on physicochemical properties, toxicity and scenario-specific exposure information. However, such data are yet not readily available, and tools that can handle data gaps in a structured way to ensure transparent risk analysis for industrial and regulatory decision making are needed. This paper proposes such a quantitative risk prioritisation tool, based on a multi-criteria decision analysis algorithm, which combines advanced exposure and dose-response modelling to calculate margins of exposure (MoE) for a number of MN in order to rank their occupational risks. We demonstrated the tool in a number of workplace exposure scenarios (ES) involving the production and handling of nanoscale titanium dioxide, zinc oxide (ZnO), silver and multi-walled carbon nanotubes. The results of this application demonstrated that bag/bin filling, manual un/loading and dumping of large amounts of dry powders led to high emissions, which resulted in high risk associated with these ES. The ZnO MN revealed considerable hazard potential in vivo, which significantly influenced the risk prioritisation results. In order to study how variations in the input data affect our results, we performed probabilistic Monte Carlo sensitivity/uncertainty analysis, which demonstrated that the performance of the proposed model is stable against changes in the exposure and hazard input variables.

Aggregation cognitive maps procedure for group decision analysis

Purpose – Cognitive maps are used in group decision processes to structure problems. The problem structuring methods helps decision makers to improve the comprehension of the problem, identifying alternative actions and conflicts. However, represents the individual perceptions in a representative group decision into a single structure can be a complex task. The paper aims to discuss these issues. Design/methodology/approach – The objective of this paper is to improve the process of discussion, obtaining the interests and views of the participants and provide parameters to assist the analyst to guide the process. Furthermore, it is possible to analyze how participants are aligned or diverge from the group. The literature review presents some approaches for cognitive maps analysis, but there is a lack of structured methods to analyze them. This paper proposes a structure procedure for the aggregation of cognitive maps in three parts: workshop to generate individual maps, the aggregation of individual maps and the refinement of the global map. Findings – An example illustrates the application of the proposed method and shows the construction of a global map that summarizes the concepts that participants consider important. Originality/value – This paper presents a new procedure that allows reducing the bias of the analyst in the aggregation of individual cognitive maps maintaining the relevant information and allows decision makers know and approve the aggregation procedure.

Integrated sustainability assessment for chemical processes

Policies on sustainable development have resulted in the wide concern about economic, safety, and environmental-friendly chemical production. This work focuses on the development of a holistic methodology that enables the evaluation and comparison of process sustainability in an integrated system. This methodology is proposed based on material and energy flows, process parameters, and process configuration. It uses a set of criteria, including inherent safety, potential environmental impact, and economic aspects. These criteria as the basis for determining the integrated index can be used to perform sustainability assessment for process alternatives under investigation. The multi-criteria decision analysis procedure is presented to conduct the integrated assessment based on qualitative and quantitative analysis. As a case study, ethanol production process, i.e., ethylene-derived feedstock process (A1) and straw cellulose-derived feedstock process (A2) are used to illustrate the proposed methodology. Results showed that A1 had advantage over A2 for the economic aspect while A2 had better performance in the environmental and safety aspects. A2 is the prior option from the point of view of comprehensive evaluation.

Ecotourism planning in Lantau Island using multiple criteria decision analysis with geographic information system

Hong Kong has great potential to develop ecotourism as an alternate tourism experience. In order to provide visitors with satisfaction and conserve and sustain natural resources, a comprehensive zoning plan is indispensable to identify areas for various purposes and activities. Geographic information system combined with multi-criteria decision analysis procedure can be used to formulate these plans in an objective and efficient way. This study used this approach to objectively identify potential sites for various ecotourism activities and tourism development potential in Lantau Island, Hong Kong SAR. The results were then used to evaluate the Lantau development plan proposed by the government. By integrating with quality conservation information, the island was further classified into four zones namely sanctuary, nature conservation, outdoor recreation, and tourism development through multi-objective analysis. The results showed that proposed sites for various recreational activities are of medium to high suitability, while other potential sites with high suitability were revealed. In addition, sites with conflicting objectives and those required further protection were also identified. The results can be used as an unbiased guide for Lantau development. This study also demonstrated ecotourism planning and development can be practically supported by geo-information tools combined with proper multi-criteria decision analysis procedures based on which better decision can be made.

Resolving coastal conflicts using marine spatial planning

We applied marine spatial planning (MSP) to manage conflicts in a multi-use coastal area of Kenya. MSP involves several steps which were supported by using geographical information systems (GISs), multi-criteria decision analysis (MCDA) and optimization. GIS was used in identifying overlapping coastal uses and mapping conflict hotspots. MCDA was used to incorporate the preferences of user groups and managers into a formal decision analysis procedure. Optimization was applied in generating optimal allocation alternatives to competing uses. Through this analysis three important objectives that build a foundation for future planning of Kenya's coastal waters were achieved: 1) engaging competing stakeholders; 2) illustrating how MSP can be adapted to aid decision-making in multi-use coastal regions; and 3) developing a draft coastal use allocation plan. The successful application of MSP to resolve conflicts in coastal regions depends on the level of stakeholder involvement, data availability and the existing knowledge base.