Multicriterion Decision in Management

Pomerol, Jean‐Charles; Barba-Romero, Sergio

doi:10.1007/978-1-4615-4459-3

Cited by 262 publications

(35 citation statements)

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“…For example, MCDM methods have been developed to solve conflicting preferences among criteria (Keeney and Raiffa 1976). Rational decisionmaking requires combining both objective and subjective criterion (Pomerol and Barba-Romero 2000), most notably in a collaborative participatory framework for which MCDM methods can provide useful framework (Saaty 1994;Malczewski 2002;Tangestani 2004;Sadiq and Husain 2005). The study area is dominated by forests, where most of the stakeholders are local indigenous people, and their dependence on forest resources is immense.…”

Section: Introductionmentioning

confidence: 99%

Fire risk evaluation using multicriteria analysis—a case study

Vadrevu

Eaturu

Badarinath

2009

Environ Monit Assess

159

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Forest fires are one of the major causes of ecological disturbance and environmental concerns in tropical deciduous forests of south India. In this study, we use fuzzy set theory integrated with decision-making algorithm in a Geographic Information Systems (GIS) framework to map forest fire risk. Fuzzy set theory implements classes or groupings of data with boundaries that are not sharply defined (i.e., fuzzy) and consists of a rule base, membership functions, and an inference procedure. We used satellite remote sensing datasets in conjunction with topographic, vegetation, climate, and socioeconomic datasets to infer the causative factors of fires. Spatial-level data on these biophysical and socioeconomic parameters have been aggregated at the district level and have been organized in a GIS framework. A participatory multicriteria decision-making approach involving Analytical Hierarchy Process has been designed to arrive at a decision matrix that identified the important causative factors of fires. These expert judgments were then integrated using spatial fuzzy decision-making algorithm to map the forest fire risk. Results from this study were quite useful in identifying potential "hotspots" of fire risk, where forest fire protection measures can be taken in advance. Further, this study also demonstrates the potential of multicriteria analysis integrated with GIS as an effective tool in assessing "where and when" forest fires will most likely occur.

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Section: Introductionmentioning

confidence: 99%

Fire risk evaluation using multicriteria analysis—a case study

Vadrevu

Eaturu

Badarinath

2009

Environ Monit Assess

159

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“…The weights of each of the 10 performance indicators at each of the gauge site depend on the formulated pay off matrix i.e., RCMs versus performance indicator array. The estimation of weights for each of the performance indicator through this approach does not demand any human intervention, which will eliminate any possible bias towards any indicator (Pomerol and Romero, 2000;Raju and Kumar, 2014). Moreover, the variation of weights allows the decision makers to understand the importance of each indicator.…”

Section: Entropy Methodsmentioning

confidence: 99%

Spatial Extent of Future Changes in the Hydrologic Cycle Components in Ganga Basin using Ranked CORDEX RCMs

Anand

Devak

Gosain

et al. 2017

Preprint

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Abstract. The negative impacts of climate change are expected to be felt over wide range of spatial scales, ranging from small basins to large watersheds, which can possibly be detrimental to the services that natural water systems provide to the society. The impact assessment of future climate change on hydrologic response is essential for the 10 decision makers while carrying out management and various adaptation strategies in a changing climate. While, the availability of finer scale projections from regional climate models (RCM) has been a boon to study changing climate conditions, these climate models are subjected to large number of uncertainties, which demands a careful selection of an appropriate climate model, however. In an effort to account for these uncertainties and select suitable climate models, a multi-criteria ranking approach is deployed in this study. Ranking of CORDEX RCMs 15 is done based on its ability to generate hydrologic components of the basin, i.e., runoff simulations using Soil Water Assessment Tool (SWAT) model, by deploying Entropy and PROMETHEE-2 methods. The spatial extent of changes in the different components of hydrologic cycle is examined over the Ganga river basin, using the top three ranked RCMs, for a period from January 2021 to December 2100. It is observed that for monsoon months (June, July, August and September), future annual mean surface runoff will decrease substantially (-50 % to -20 10%), while the flows for post-monsoon months (October, November and December) are projected to increase (10-20 %). While, extremes are seen to be increasing during the non-monsoon months, a substantial decrease in medium events is also highlighted. The increase in wet extremes is majorly supplemented by the increased snowmelt runoff during those months. Snowmelt is projected to increase during the months of November to March, with the month of December witnessing 3-4 times increase in the flow. Base flow and recharge are 25 alarmingly decreasing over the basin. Major loss of recharge is expected to occur in central part of the basin. The present study offers a more reliable regional hydrologic impact assessment with quantifications of future dramatic changes in different hydrological sub-system and its mass-transfer, which will help in quantifying the changes in hydrological components in response to climate change changes in the major basin Ganga, and shall provide the water managers with substantive information, required to develop ameliorative strategies. 30

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“…There are many techniques to elicit the weights, such as the weighted evaluation technique, the eigenvector method, the analytic hierarchy process (AHP) method, the weighted least square method and so forth [21]. However, most of them entail subjectivity in assigning weights to criteria due to using opinion of experts, and because of that, there is no guarantee that these weights will be replicated when another person or team estimates them [22] In order to guarantee the consistency of the model, this study employs Entropy weighting method -an objective weighting method [23] to elicit the weights of evaluation criteria. The calculation steps are as following as in [21]: A multicriteria decision making problem with m alternative and n criteria can be expressed in decision matrix as Equation (6).…”

Section: Combination Of Weighting Factors Using Entropy Weighting Methodsmentioning

confidence: 99%

MEMRECS—A Sustainable View for Metal Recycling from Waste Printed Circuit Boards

Le¹,

Yamasue²,

Okumura³

et al. 2013

JEP

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This study analyses the metal recyclability from waste Printed Circuit Boards (PCBs) with three material recycling quoting approaches: Material Recycling Efficiency (MRE), Resource Recovery Efficiency (RRE), and Quotes for Environmentally Weighted Recyclability (QWERTY). The results indicate that MRE is likely inapplicable to quoting the metal recyclability of waste PCBs because it makes the recycling of any metal equal to each other (e.g. recycling of 1 kg of gold is as important as recycling of 1 kg of iron). RRE and QWERTY can overcome the poor yardstick of MRE because they concern not only the weight of recycled materials but also the contribution of recycled materials to the natural resource conservation and the environmental impact reduction, respectively. These two approaches, however, report an extremely different result, that makes the target stakeholders get confused with which material recycled. From the findings of the aforementioned analysis, this study proposes the Model for Evaluating Metal Recycling Efficiency from Complex Scraps (MEMRECS) as a new approach to quotes the metal recycling performance. MEMRECS allows the trade-offs between three criteria: mass, environmental impacts and natural resources conservation, hence it can provide the result in a sustainable sound manner. MEMRECS clearly models and enhances the role of natural resources conservation aspect rather than QWERTY does.

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Multicriterion Decision in Management

Cited by 262 publications

References 0 publications

Fire risk evaluation using multicriteria analysis—a case study

Fire risk evaluation using multicriteria analysis—a case study

Spatial Extent of Future Changes in the Hydrologic Cycle Components in Ganga Basin using Ranked CORDEX RCMs

MEMRECS—A Sustainable View for Metal Recycling from Waste Printed Circuit Boards

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