Decision making under uncertainty using PEES–fuzzy AHP–fuzzy TOPSIS methodology for landfill location selection

The location selection for landfill municipal solid waste is an important issue in waste management. Selection of the optimal location requires consideration of multiple alternative solutions and evaluation factors because of system complexity. Further, ranking of the alternative locations and selection of the most optimal and efficient locations for landfill waste are an important multi-criteria decision-making problem. In this study, the candidate locations for landfill are determined based on Political, Economical, Environmental and Social factors are assessed through decision-makers’ opinion and by the methodology that incorporates fuzzy analytic hierarchy process (fuzzy AHP) and fuzzy technique for order preference by similarity to ideal solution (fuzzy TOPSIS). Specifically, the fuzzy AHP technique is applied to determine the weights of selected criteria impacting the location selection process, and the fuzzy AHP is adapted to model the linguistic vagueness and ambiguity, which can also be expressed as triangular fuzzy numbers. Furthermore, fuzzy TOPSIS technique is employed to rank the alternative locations. The applicability of this methodology is demonstrated by a case study of landfill waste location selection in the region of Casablanca, Morocco, and the results are compared with other techniques. Finally, to complete the treatment, a sensitivity analysis is performed to examine the impact of the preferences given by decision-makers to choose the best location.     

A hybrid approach using ISM and fuzzy TOPSIS for the selection of reverse logistics provider

Return of used products is becoming an important logistics activity due to government legislation and increasing awareness among the people to protect the environment and reduce waste. For industries, the management of return flow usually requires a specialized infrastructure with special information systems for tracking and dedicated equipment for the processing of returns. Therefore, industries are turning to third-party reverse logistics providers (3PRLPs). In this study, a multi-criteria group decision-making (MCGDM) model in fuzzy environment is developed to guide the selection process of best 3PRLP. The interactions among the criteria are also analyzed before arriving at a decision for the selection of 3PRLP from among 15 alternatives. The analysis is done through Interpretive Structural Modeling (ISM) and fuzzy technique for order preference by similarity to ideal solution (TOPSIS). Finally the effectiveness of the model is illustrated using a case study on battery manufacturing industry in India.     

Integrating the AHP and TOPSIS decision processes for evaluating the optimal collection strategy in reverse logistic for the TPI

This study presents processes to evaluate the optimal collecting strategy (CS) in reverse logistic (RL) for the downstream part of the Taiwan photovoltaic industry (TPI). It combines the analytic hierarchy process (AHP) with the technique for ordering preference by similarity to the ideal solution (TOPSIS). The criteria and sub-criteria were initially established to assess the related benefits, opportunities, costs, and risks (BOCR). AHP was then used to obtain the weightings of the criteria and sub-criteria and TOPSIS was used to rank the optimal collection strategy in terms of its overall evaluation criteria. The AHP and TOPSIS method provides decision makers with a valuable reference for assessing the optimal collection strategy of TPI downstream. The results of the study should provide decision makers in the downstream TPI with academic support and valuable guidance for evaluating their collection program and obtain optimal strategies for administering RL practices.     

A multi-criteria decision analysis of solid waste treatment options in Pakistan: Lahore City—a case in point

Population of the world is increasing day by day, resulting in enormous amount of waste production. In the modern age of great technological advancements, there needs to be a systematic method to keep the environment clean. The waste management activities, i.e., collection, transport and disposal, pose a great challenge to the waste managers as they have to factor in various eclectic factors such as land availability, facilities available, budget, time required and the impact it would have on the environment, while tackling this problem. Lahore, despite being the most developed city of Pakistan, does not have a suitable solid waste management system. An increasing population leads to more waste generation, and in Lahore the situation is no different. Several waste management companies are working in the city, but as of yet they have not been able to make significant inroads to completely eradicate the problem. The aim of this paper is to suggest a suitable way for dealing with the waste. To accomplish this aim, a hierarchy-based model is used, considering six criteria and five alternatives. We used multi-criteria decision analysis to decide among different waste management alternatives. Forecasting has been used to find the population and waste produced over the years. Analytical hierarchy process (AHP) and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) are used to rank the feasible alternative. The results show that the population and waste were increasing drastically. Aerobic digestion was ranked as the best alternative for waste management according to AHP and TOPSIS, but there is great variation among the rank of other alternatives.     

The optimal dam site selection using a group decision-making method through fuzzy TOPSIS model

The complex and controversial task of selecting a dam site in a river basin can be successfully achieved using science-informed multi-criteria decision-making (MCDM) techniques. In this paper, we describe the application of the group fuzzy TOPSIS model for optimal ranking of the case study of Kandoleh dam sites in Kermanshah province, Iran, involving 18 input criteria. In this study, decision-making committee was made up of 20 involved decision makers. The comments of four non-biased, external experts in dam site selection were also used. The triangular fuzzy numbers were used to apply experts’ opinions on the selection criteria. In total, four alternative sites were assessed based on the technical, economic, social and environmental considerations and the data were analyzed using fuzzy TOPSIS MCDM model. Ranking results were compared with multi-criteria decision-making models, including the ELimination and Choice Expressing the REality and simple additive weighting. This logical, open and transparent framework provides a science-informed decision-making approach for complex problems such as optimal dam site selection. Finally, using sensitivity analysis, local studies and group discussions, we demonstrated the multiple benefits of the proposed novel method for a science-informed, open and transparent method for optimal ranking of the dam site candidates.     

Selection of optimum fish oil fuel blend to reduce the greenhouse gas emissions in an IC engine—A hybrid multiple criteria decision aid approach

The increasing demand on energy due to population growth and rising of living standards has led to considerable use of fossil fuels which has in turn, had an adverse impact on environmental pollution and depletion of fossil fuels in Internal Combustion (IC) engine sector. Alternative fuel blend evaluation in IC engine fuel technologies is a very important strategic decision involving decisions balancing within a number of criteria and opinions from different decision maker of IC engine experts. The selection of appropriate source of biodiesel and proper blending of biodiesel plays a major role in alternate energy production. This paper describes an application of hybrid Multi Criteria Decision Making (MCDM) technique for the selection of optimum biodiesel blend in the IC engine. The proposed model, Analytical Network Process (ANP) is integrated with Technique for Order Performance by Similarity to Ideal Solution (TOPSIS) to evaluate the optimum blend. Here the ANP is used to determine the relative weights of the criteria, whereas TOPSIS is used for obtaining the final ranking of alternative blends. An efficient pair-wise comparison process and ranking of alternatives can be achieved for optimum blend selection through the integration of ANP and TOPSIS. The obtained preference order for the blends are as B20 > B40 > Diesel > B60 > B80 > B100. This paper highlights a new insight into MCDM techniques to evaluate the best fuel blend for the decision makers such as engine manufactures and R&D engineers to meet the fuel economy and emission norms to empower the green revolution.     

Hospital site selection using fuzzy AHP and its derivatives

Environmental managers are commonly faced with sophisticated decisions, such as choosing the location of a new facility subject to multiple conflicting criteria. This paper considers the specific problem of creating a well-distributed network of hospitals that delivers its services to the target population with minimal time, pollution and cost. We develop a Multi-Criteria Decision Analysis process that combines Geographical Information System (GIS) analysis with the Fuzzy Analytical Hierarchy Process (FAHP), and use this process to determine the optimum site for a new hospital in the Tehran urban area. The GIS was used to calculate and classify governing criteria, while FAHP was used to evaluate the decision factors and their impacts on alternative sites. Three methods were used to estimate the total weights and priorities of the candidate sites: fuzzy extent analysis, center-of-area defuzzification, and the α-cut method. The three methods yield identical priorities for the five alternatives considered. Fuzzy extent analysis provides less discriminating power, but is simpler to implement and compute than the other two methods. The α-cut method is more complicated, but integrates the uncertainty and overall attitude of the decision-maker. The usefulness of the new hospital site is evaluated by computing an accessibility index for each pixel in the GIS, defined as the ratio of population density to travel time. With the addition of a new hospital at the optimum site, this index improved over about 6.5 percent of the geographical area.     

A fuzzy multi criteria approach for evaluating green supplier's performance in green supply chain with linguistic preferences

Today's international business environment has forced many firms to focus on supply chain management to gain a competitive advantage. During recent years, supplier selection process in the supply chain has become a key strategic consideration. With the growing worldwide awareness of environmental protection and the corresponding increase in legislation and regulations, green purchasing has become an important issue for companies to gain environmental sustainability. Traditionally, companies consider criteria such as price, quality and lead time, when evaluating supplier performance and do not give enough attention to environmental criteria as a means to evaluate suppliers. Now, many companies have begun to implement green supply chain management (GSCM) and to consider environmental issues and the measurement of their suppliers’ environmental performance. This paper examines GSCM to propose a fuzzy multi criteria approach for green suppliers’ evaluation. We apply fuzzy set theory to translate the subjective human perceptions into a solid crisp value. These linguistic preferences are combined through fuzzy TOPSIS to generate an overall performance score for each supplier. A numerical example is presented to demonstrate the effectiveness of the proposed approach.     

Groundwater vulnerability assessment using an improved DRASTIC method in GIS

Groundwater management can be effectively conducted by using groundwater contamination map assessment. In this study, a modified DRASTIC approach using geographic information system (GIS) was applied to evaluate groundwater vulnerability in Kerman plain (Iran). The Wilcoxon rank-sum nonparametric statistical test was applied to modify the rates of DRASTIC. In addition, the analytic hierarchy process (AHP) method was employed to evaluate the validity of the criteria and sub criteria of all the parameters of the DRASTIC model, which proposed as an alternative treatment of the imprecision demands. The GIS offers spatial analysis in which the multi index evaluation can be effectively conducted through the AHP. The non-point source pollution was effectively determined by the modified DRASTIC method compared with the traditional method. The regression coefficient revealed the relationship between the vulnerability index and the nitrate concentration. The best result was obtained by using AHP–AHP, followed by DRASTIC–AHP, modified DRASTIC–AHP, and AHP–DRASTIC models. In this study, the DRASTIC method failed to provide satisfactory result. Additionally, by using both the original DRASTIC and the modified DRASTIC methods in the study area, AHP–AHP performed highly in the Kerman plain, suggesting that the southern and south east parts of the area considerably calls for conservation against contamination.     

Sustainable Water Resources Management in a Conflict Resolution Framework1

Abstract: A decision support system for sustainable water resources management in a water conflict resolution framework is developed to identify and evaluate a range of acceptable alternatives for the Geum River Basin in Korea and to facilitate strategies that will result in sustainable water resource management. Working with stakeholders in a “shared vision modeling” framework, sustainable management strategies are created to illustrate system tradeoffs as well as long‐term system planning. A multi‐criterion decision‐making (MCDM) approach using subjective scales is utilized to evaluate the complex water resource allocation and management tradeoffs between stakeholders and system objectives. The procedures used in this study include the development of a “shared vision model,” a simulated decision‐making support system (as a tool for sustainable water management strategies associated with water conflicts, management options, and planning criteria), and the application of MCDM techniques for evaluating alternatives provided by the model. The research results demonstrate the utility of the sustainable water resource management model in aid of MCDM techniques in facilitating flexibility during initial stages of alternative identification and evaluation in a basin suffering from severe water conflicts.     

Application of Multiattribute Decision-Making Methods for the Determination of Relative Significance Factor of Impact Categories

A relative significance factor (f _i ) of an impact category is the external weight of the impact category. The objective of this study is to propose a systematic and easy-to-use method for the determination of f _i . Multiattribute decision-making (MADM) methods including the analytical hierarchy process (AHP), the rank-order centroid method, and the fuzzy method were evaluated for this purpose. The results and practical aspects of using the three methods are compared. Each method shows the same trend, with minor differences in the value of f _i . Thus, all three methods can be applied to the determination of f _i . The rank order centroid method reduces the number of pairwise comparisons by placing the alternatives in order, although it has inherent weakness over the fuzzy method in expressing the degree of vagueness associated with assigning weights to criteria and alternatives. The rank order centroid method is considered a practical method for the determination of f _i because it is easier and simpler to use compared to the AHP and the fuzzy method.     

Using triple bottom line metrics and multi-criteria methodology in corporate settings

With the growing importance of environmental sustainability in the corporate sector, businesses are compelled to progress from assessing and benchmarking their environmental impact to making decisions on how to prioritize impact reduction alternatives. Most often, business decisions are driven by financial metrics, but with sustainability improvements becoming a business goal, it is also important to assess metrics from environmental and social spheres; nevertheless, practically and systematically performing such an assessment is challenging. We present an application of a multi-criteria decision analysis (MCDA) method that addresses the aforementioned challenges in a corporate setting. Our case study company – one of the largest inland marine freight carriers in the United States – promotes a business culture focused on financially viable, yet socially and environmentally responsible solutions. Thus, we combine life cycle analysis (LCA), financial calculation methods, and corporate surveys to quantify environmental, economic, and social performance measures, respectively. Multiattribute utility theory is integrated with analytic hierarchy processes (AHPs) and fuzzy analysis to create a carefully designed framework for corporations with diverse groups of stakeholders. With company leadership, implementation is feasible and successful at prioritizing alternatives among diverse stakeholders. The process provides a platform for negotiation and promotes discussions on decision drivers. The use of MCDA methodologies promoted the inclusion of a suite of metrics that aligned with the company's sense of social and environmental responsibility, generating an in-depth analysis of the alternatives that factored in other things besides economics. Return-on-investments (ROI) calculations, the typical approach used in the corporate setting, would have required significantly less time and effort from the company, but the results of our MCDA application indicated that inclusion of triple bottom line metrics delve deeper into stakeholder preferences. Thus, our case study company gained a holistic view of the candidate alternatives, in addition to creating a platform for structured discussions about company goals and priorities.     

MULTICRITERION DECISION MAKING FOR FLOOD CONTROL OPERATIONS: THEORY AND APPLICATIONS1

ABSTRACT: Flood control operations are generally complex in nature, as they are often associated with a large quantity of uncertain factors in combination of noncommensurable criteria. It has been found that the use of fuzzy set theory coupled with multicriterion decision making (MCDM) methods is very promising. In this paper, a multicriterion fuzzy recognition model is established for flood control operations. A subjective preference and iterative weights method is proposed for weight assessment. First, an initial solution of criteria weights, which is directly analyzed from the selected alternatives, is obtained by using the proposed fuzzy recognition model. Then, according to their knowledge related to real time flood operations, operators may modify the initial weights if necessary. When the relative membership grades of alternatives belonging to all rankings are fixed, a defuzzification equation is used to calculate the rank feature value vector. Based on the rank feature value vector, one can evaluate the alternative set. Two flood operation cases are provided to illustrate the application of the proposed model. With the incorporation of the operator's knowledge related to flood operations, the proposed model is flexible in giving weights and realizes more practical flood control operations.     

Participatory Model Calibration for Improving Resource Management Systems: Case Study of Rainwater Harvesting in an Indian Village

While planning resource management systems in rural areas, it is important to consider criteria that are specific to the local social conditions. Such criteria might change from one region to another and are hence best identified using a participatory approach. In this work, we propose a participatory framework to identify such criteria and derive their weights. These identified criteria and their weights are used as parameters to develop a quantitative model for evaluating efficiency of each system. Such a model can serve as a support tool for stakeholders to simulate and analyze “what‐if” scenarios, evaluate alternatives, and select one which best satisfies their requirements. We use existing systems to test the model by comparing efficiencies evaluated by the model to efficiencies perceived by the stakeholders. The model is calibrated by repeating the process until statistically significant correlation is achieved between evaluated and perceived efficiencies. The novelty of the proposed framework lies in treating efficiencies perceived by the stakeholders as the ground truth since they know these systems well and are their ultimate users. The framework is successfully demonstrated using case study of rainwater harvesting (RWH) systems in an Indian village. The resulting calibrated model can be used to plan new RWH systems in this region and similar regions elsewhere. The framework can be used to plan other resource management systems in various regions.     

Optimization of regional economic and environmental systems under fuzzy and random uncertainties

Environmental problems associated with socio-economic development have been growing concerns faced by many regional and/or national authorities. However, effective planning may encounter difficulties since uncertainties existing in a number of impact factors and pollution-related processes are often not well acknowledged and reflected. This study advances an interval-fuzzy chance-constrained programming (IFCP) method for planning regional economic and environmental systems, where uncertainties presented as intervals, fuzzy sets and probability distributions can be tackled. The developed method is applied to a real-world case for economic and environmental planning in the New Binhai District in the Municipality of Tianjin, China. Two scenarios based on multiple environmental constraints are examined. The results can help identify desired alternatives for planning regional development strategies, where compromised schemes are provided under an integrated consideration of economic efficiency and environmental protection under multiple uncertainties.     

Freebies,freedom and fundamental change: resistance to neoliberal environmentalism in large “green” corporations

Despite the professed concern of many governments, businesses and individuals – and the recent publication of another alarming report from the IPCC – inaction on climate change remains a significant concern. For many, the problem is rooted in a neoliberal account of social change. Neoliberal environmentalism is the dominant approach to environmental issues but it is often blamed for the continuing failure of climate change policy in general and behaviour change initiatives in particular. This paper explores the dynamics of this dominant discourse through an examination of environmentalism in the large “green” corporation. Specifically, it uses discourse analysis to investigate so-called “climate champion” schemes and considers examples of resistance to the dominant neoliberal discourse. The paper finds that many of the champions did resist the basic components of neoliberal environmentalism. They challenged the principles of self-interest, self-rule and incremental change, and they talked about the possibility of enforced action. However, this resistance was limited in a number of different ways. The paper suggests that the workplace does play a role in restricting resistance but that there are more fundamental issues that need to be addressed if we hope to pursue an alternative approach to environmental problems such as climate change.     

Multi-criteria analysis for improving strategic environmental assessment of water programmes. A case study in semi-arid region of Brazil

Multi-criteria analysis (MCA) is a family of decision-making tools that can be used in strategic environmental assessment (SEA) procedures to ensure that environmental, social and economic aspects are integrated into the design of human development strategies and planning, in order to increase the contribution of the environment and natural resources to poverty reduction. The aim of this paper is to highlight the contribution of a particular multi-criteria technique, the analytic hierarchy process (AHP), in two stages of the SEA procedure applied to water programmes in developing countries: the comparison of alternatives and monitoring. This proposal was validated through its application to a case study in Brazilian semi-arid region. The objective was to select and subsequently monitor the most appropriate programme for safe water availability. On the basis of the SEA results, a project was identified and implemented with successful results. In terms of comparisons of alternatives, AHP meets the requirements of human development programme assessment, including the importance of simplicity, a multidisciplinary and flexible approach, and a focus on the beneficiaries' concerns. With respect to monitoring, the study shows that AHP contributes to SEA by identifying the most appropriate indicators, in order to control the impacts of a project.     

A stochastic fuzzy chance-constrained programming model for energy–environment system planning and management in the City of Beijing

A stochastic and fuzzy chance-constrained programming (SFCCP) model was developed in this study for supporting energy–environment management in the city of Beijing, China. SFCCP was capable of tackling the variables in constraints as fuzzy random variables, which were integration of randomness and vagueness. SFCCP was applied to an energy–environment management system in the city of Beijing. The study results indicated that SFCCP was useful in helping decision makers gain in-depth insights into proposed management system and establish environment-friendly energy allocation alternatives. The application of SFCCP is expected to provide a good demonstration to energy–environment management problems under complex uncertainties.     

Green financing,interrupted. Potential directions for sustainable finance in Luxembourg

ABSTRACT

This paper has a quintessentially explorative character. It aims at identifying existing as well as potential (yet missing) links between the finance industry and local businesses that aspire to more sustainable economic practices. Building on the observation that green investments have been gaining weight in global investors’ strategies, we analyse how sustainable – in the most comprehensive sense of the word – green investments could ultimately be(come), when green assets are still managed according to the logic of “financialised finance”. This latter’s technologies of commodification, securitisation and derivatives-trading allegedly oppose alternative economic practices that pursue economic sustainability through social and environmental gains. In contrast, we investigate how the finance industry relates to alternative financial practices, products and organisations that offer sustainability-oriented financing services, – for example, regional banks, cooperatives and the like, – with a specific focus on green, social and solidarity businesses. Both approaches subscribe to apparently contradictory ideologies. We establish a beneficial dialogue between the opposing models of “green capitalism” and “alternative economies” so as to identify potential points of intersection. The context of Luxembourg’s local/regional economies provides a great opportunity to empirically access three levels of investigation: the private sector, the public sector and an international financial centre, a key facilitator for green finance, thus utilising insights from the concept of bricolage. Whilst supporters of Luxembourg’s emerging green finance profile recognise its positive impact on the small country’s national branding, in combination with economic stimuli, more critical commentators point to pure “green washing” effects.     

Techno-environmental risks and ecological modernisation in “double-risk” societies: reconceptualising Ulrich Beck’s risk society thesis

By utilising a relatively underused framework developed by Maurie J. Cohen (1997. Risk society and ecological modernisation alternative visions for post-industrial nations. Futures, 29 (2), 105–119), this theoretical paper joins two of the most debated theories of environmental politics – ecological modernisation (EM) and Ulrich Beck’s risk society thesis – into a unified framework and problematises some of their implicit assumptions to theoretically introduce the notion of a “double-risk” society. In addition, it explains the differences between the traditional “Risk Society” theorised by the German sociologist Ulrich Beck and the newly introduced concept of a “double-risk” society. The arguments put forward in this paper provide some fresh perspectives facilitating the study of the techno-environmental risks and other ecological problems faced by “double-risk” societies. Theoretically, this paper adds to both EM theory and the risk society thesis as the generalisability of their existing versions is limited precisely because they fail to address some important social changes at the global structural level.