Combining GIS with fuzzy multicriteria decision-making for landfill siting in a fast-growing urban region

Landfill siting is a difficult, complex, tedious, and protracted process requiring evaluation of many different criteria. This paper presents a fuzzy multicriteria decision analysis alongside with a geospatial analysis for the selection of landfill sites. It employs a two-stage analysis synergistically to form a spatial decision support system (SDSS) for waste management in a fast-growing urban region, south Texas. The first-stage analysis makes use of the thematic maps in Geographical information system (GIS) in conjunction with environmental, biophysical, ecological, and socioeconomic variables leading to support the second-stage analysis using the fuzzy multicriteria decision-making (FMCDM) as a tool. It differs from the conventional methods of integrating GIS with MCDM for landfill selection because the approach follows two sequential steps rather than a full-integrated scheme. The case study was made for the city of Harlingen in south Texas, which is rapidly evolving into a large urban area due to its vantage position near the US-Mexico borderlands. The purpose of GIS was to perform an initial screening process to eliminate unsuitable land followed by utilization of FMCDM method to identify the most suitable site using the information provided by the regional experts with reference to five chosen criteria. Research findings show that the proposed SDSS may aid in recognizing the pros and cons of potential areas for the localization of landfill sites in any study region. Based on initial GIS screening and final FMCDM assessment, "site 1" was selected as the most suitable site for the new landfill in the suburban area of the City of Harlingen. Sensitivity analysis was performed using Monte Carlo simulation where the decision weights associated with all criteria were varied to investigate their relative impacts on the rank ordering of the potential sites in the second stage. Despite variations of the decision weights within a range of 20%, it shows that "site 1" remains its comparative advantage in the final site selection process.     

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.     

A distance-based uncertainty analysis approach to multi-criteria decision analysis for water resource decision making

The choice among alternative water supply sources is generally based on the fundamental objective of maximising the ratio of benefits to costs. There is, however, a need to consider sustainability, the environment and social implications in regional water resources planning, in addition to economics. In order to achieve this, multi-criteria decision analysis (MCDA) techniques can be used. Various sources of uncertainty exist in the application of MCDA methods, including the selection of the MCDA method, elicitation of criteria weights and assignment of criteria performance values. The focus of this paper is on the uncertainty in the criteria weights. Sensitivity analysis can be used to analyse the effects of uncertainties associated with the criteria weights. Two existing sensitivity methods are described in this paper and a new distance-based approach is proposed which overcomes limitations of these methods. The benefits of the proposed approach are the concurrent alteration of the criteria weights, the applicability of the method to a range of MCDA techniques and the identification of the most critical criteria weights. The existing and proposed methods are applied to three case studies and the results indicate that simultaneous consideration of the uncertainty in the criteria weights should be an integral part of the decision making process.     

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.     

An analytic network process approach for locating undesirable facilities: an example from Istanbul, Turkey

Locating an undesirable facility is a sophisticated problem, for the evaluation procedures involve several objectives and the solution to the problem calls for some compromises to be made between probable conflicting criteria. This paper addresses the problem of undesirable facility location selection using the analytic network process (ANP), a multi-criteria decision-making technique. The ANP technique enables us to consider both qualitative and quantitative criteria as well as the interdependencies and feedbacks. A number of criteria (benefits, opportunities, costs and risks) and their sub-criteria are considered for siting a new facility with which this study has dealt. The questions of what criteria would be considered and what the interdependencies between these criteria and their weights would be were discussed and determined via interviews with some competent authorities of the Istanbul Municipality and of two environmental organizations. Four representative locations were evaluated and the most convenient one was selected. This was followed by the sensitivity analyses of the results.     

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.     

FUZZY DECISION MAKING IN GROUND WATER NITRATE RISK MANAGEMENT1

ABSTRACT: Ground water nitrate contamination is widespread in the United States and especially prevalent in agriculture-intensive areas such as the Midwest. To reduce human health risks (i.e., methemoglobinemia and cancer risks) from nitrates in ground water supplies, several nitrate risk-management strategies can be developed based on acceptable levels of human health risks, the reasonableness of the cost required for risk reduction, and the technical feasibility of nitrate-control methods. However, due to a lack of available information, assessing risk, cost, and technical feasibility contains elements of uncertainty. In this paper, a nitrate risk-management methodology using fuzzy sets in combination with a multicriterion decision-making (MCDM) technique is developed to assist decision makers in evaluating, with uncertain information, possible regulatory actions along with the various nitrate risk-management strategies in order to determine an appropriate strategy. The methodology is illustrated using data from a community with a nitrate water-quality problem.     

A comparative analysis of methods to represent uncertainty in estimating the cost of constructing wastewater treatment plants

Prediction of construction cost of wastewater treatment facilities could be influential for the economic feasibility of various levels of water pollution control programs. However, construction cost estimation is difficult to precisely evaluate in an uncertain environment and measured quantities are always burdened with different types of cost structures. Therefore, an understanding of the previous development of wastewater treatment plants and of the related construction cost structures of those facilities becomes essential for dealing with an effective regional water pollution control program. But deviations between the observed values and the estimated values are supposed to be due to measurement errors only in the conventional regression models. The inherent uncertainties of the underlying cost structure, where the human estimation is influential, are rarely explored. This paper is designed to recast a well-known problem of construction cost estimation for both domestic and industrial wastewater treatment plants via a comparative framework. Comparisons were made for three technologies of regression analyses, including the conventional least squares regression method, the fuzzy linear regression method, and the newly derived fuzzy goal regression method. The case study, incorporating a complete database with 48 domestic wastewater treatment plants and 29 industrial wastewater treatment plants being collected in Taiwan, implements such a cost estimation procedure in an uncertain environment. Given that the fuzzy structure in regression estimation may account for the inherent human complexity in cost estimation, the fuzzy goal regression method does exhibit more robust results in terms of some criteria. Moderate economy of scale exists in constructing both the domestic and industrial wastewater treatment plants. Findings indicate that the optimal size of a domestic wastewater treatment plant is approximately equivalent to 15,000 m3/day (CMD) and higher in Taiwan. Yet the optimal size of an industrial wastewater treatment plant could fall in between 6000 CMD and 20,000 CMD.     

Robust Prioritization of Climate Change Adaptation Strategies Using the VIKOR Method with Objective Weights

This study proposes a robust prioritization framework for climate change adaptation strategies under uncertain climate change scenarios, using the VIseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR) method, a multi‐criteria decision‐making approach, together with the Shannon entropy‐based weights. The VIKOR method allows us to find a compromise solution between two decision strategies of maximizing group utility and minimizing individual regret, and the Shannon entropy is used to determine objective weights among multiple climate change scenarios. The proposed methodology was applied to the problem of selecting locations of subwatersheds for reusing treated wastewater (TWW) in a Korean urban watershed. Selected based on the sustainability concept, hydro‐environmental and socioeconomic indicators were used to evaluate the sustainability of TWW reuse under multiple climate change scenarios, using the hydrologic simulation model results and statistical data. Finally, sustainability scores under multiple scenarios were aggregated using the VIKOR together with the Shannon entropy‐based weights for the robust prioritization of adaptation strategies. According to the different levels of regret aversion or affinity, our results for water quality showed different sets of adaptation strategies as the best options, suggesting that our framework would help stakeholders seeking the robust options considering both the utility and regret.     

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.     

Fuzzy pricing for urban water resources: model construction and application

A rational water price system plays a crucial role in the optimal allocation of water resources. In this paper, a fuzzy pricing model for urban water resources is presented, which consists of a multi-criteria fuzzy evaluation model and a water resources price (WRP) computation model. Various factors affecting WRP are comprehensively evaluated with multiple levels and objectives in the multi-criteria fuzzy evaluation model, while the price vectors of water resources are constructed in the WRP computation model according to the definition of the bearing water price index, and then WRP is calculated. With the incorporation of an operator's knowledge, it considers iterative weights and subjective preference of operators for weight-assessment. The weights determined are more rational and the evaluation results are more realistic. Particularly, dual water supply is considered in the study. Different prices being fixed for water resources with different qualities conforms to the law of water resources value (WRV) itself. A high-quality groundwater price computation model is also proposed to provide optimal water allocation and to meet higher living standards. The developed model is applied in Jinan for evaluating its validity. The method presented in this paper offers some new directions in the research of WRP.     

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.     

COMPARISON OF ALTERNATIVE ENGINEERING DESIGNS1

ABSTRACT: Procedures are presented for comparing and evaluating alternative engineering designs for a particular water resources project. By using certain aspects of fuzzy set theory, it is possible to introduce both quantitative and qualitative considerations into the decisionmaking process. In addition, the viewpoints of the various interest groups involved with the water resources development can be realistically incorporated by the evaluation techniques for the alternative designs. Methods are given for eliminating undesirable alternatives and thereby obtaining a reduced set of possible feasible solutions to the problem. Because of the flexibility of the evaluation methods, the viable alternatives should not only satisfy economical, technical. environmental and other types of constraints, but these possible solutions should be politically feasible as well. A method is formulated for checking the sensitivity of the feasible results with respect to the factors that are considered in the analysis.     

基于指标规范值的地表水水质的模糊综合评价

传统的模糊综合评价法用于地表水水质评价,当指标数较多时需要设计很多隶属函数,设计和计算工作量皆很大,实际使用不便。在设定指标参照值和规范变换式基础上,将指标按各级标准规范值相近程度进行适当分类,只需分类设计隶属函数即可,大幅减少了计算工作量,使模糊综合评价法应用于地表水水质评价变得简化。     

The comparison of a revised Leopold matrix and fuzzy methods in environmental impact assessment,a case study: The construction of Al‐A'amiriya residential complex,Baghdad, Iraq

Environmental impact assessment (EIA) is an efficient method to recognize and alleviate the unfavorable and inevitable impacts of human activity on the environment. The EIA is dependent on expert opinions, which can be influenced by personal experience and knowledge. To evaluate this influence, we carried out EIA of 6,000 residential apartment units of Al‐A'amiriya, Baghdad, Iraq, using a revised Leopold matrix and fuzzy methods. The matrix results reflected the direct opinions of experts. The fuzzy method was developed according to the principles of expert comments. In the matrix method, the environmental impacts of each activity were evaluated by scores between −5 (very bad) to 5 (very good). The inputs to the fuzzy method were intensity and weather stability. The fuzzy estimation of the environmental impact was composed of a group of three values; P1 as the intensity, P2 as the extent, and P3 as the persistence. We gathered the expert opinions and used the Analytical Hierarchical Process to determine the weighting coefficient of each fuzzy anticipation. The matrix method was dependent on the expert opinions. The mean values of the matrix and P‐values in each column and row scores depict the impacts of a project on the environmental aspects and each element of construction on the environment. The comparison of the results indicated an average difference of 30% between the Leopold matrix and fuzzy methods. In regard to the availability and sufficiency of data, the difference was around 10%.     

RESEARCH: Optimizing the Mix of Strategies for Control of Vehicular Emissions

/ A number of strategies for the control of vehicular emissions are being considered by the Philippine government to address Metropolitan Manila's air quality problem. An analytical tool is needed for optimizing criteria pollutant reductions given the budgetary constraints. The simplest approach is to take costs and pollutant removals to be linear with each strategy's scale of activity, and this is readily solved as a linear programming problem. Another approach is to use a dynamic system of weights which shift with progressive improvements in pollutant emissions. The two approaches yield somewhat different results, suggesting the sensitivity of the solution to the assumed weights. The study also illustrates the importance of a sound methodology for evaluating priorities given to different air quality goals. One such methodology may involve a polling of expert panels and the public to gain insight into the relative importance given to competing emissions reduction goals. An informal polling of resource agency staff was conducted and discussed in this paper. The authors take the position that proper planning involves tracing intermediate steps to the final outcome and not just focusing on the latter.KEY WORDS: Vehicular emissions; Urban air quality; Emissions control; Optimization; Manila; Environmental systems analysis     

Groundwater Vulnerability Assessment for Organic Compounds: Fuzzy Multicriteria Approach for Mexico City

This study was based on a groundwater vulnerability assessment approach implemented for the Mexico City Metropolitan Area (MCMA). The approach is based on a fuzzy multicriteria procedure integrated in a geographic information system. The approach combined the potential contaminant sources with the permeability of geological materials. Initially, contaminant sources were ranked by experts through the Analytic Hierarchy Process. An aggregated contaminant sources map layer was obtained through the simple additive weighting method, using a scalar multiplication of criteria weights and binary maps showing the location of each source. A permeability map layer was obtained through the reclassification of a geology map using the respective hydraulic conductivity values, followed by a linear normalization of these values against a compatible scale. A fuzzy logic procedure was then applied to transform and combine the two map layers, resulting in a groundwater vulnerability map layer of five classes: very low, low, moderate, high, and very high. Results provided a more coherent assessment of the policy-making priorities considered when discussing the vulnerability of groundwater to organic compounds. The very high and high vulnerability areas covered a relatively small area (71 km² or 1.5% of the total study area), allowing the identification of the more critical locations. The advantage of a fuzzy logic procedure is that it enables the best possible use to be made of the information available regarding groundwater vulnerability in the MCMA.     

Combining Analytical Hierarchy Process and Agglomerative Hierarchical Clustering in Search of Expert Consensus in Green Corridors Development Management

Environmental management and planning are instrumental in resolving conflicts arising between societal needs for economic development on the one hand and for open green landscapes on the other hand. Allocating green corridors between fragmented core green areas may provide a partial solution to these conflicts. Decisions regarding green corridor development require the assessment of alternative allocations based on multiple criteria evaluations. Analytical Hierarchy Process provides a methodology for both a structured and consistent extraction of such evaluations and for the search for consensus among experts regarding weights assigned to the different criteria. Implementing this methodology using 15 Israeli experts—landscape architects, regional planners, and geographers—revealed inherent differences in expert opinions in this field beyond professional divisions. The use of Agglomerative Hierarchical Clustering allowed to identify clusters representing common decisions regarding criterion weights. Aggregating the evaluations of these clusters revealed an important dichotomy between a pragmatist approach that emphasizes the weight of statutory criteria and an ecological approach that emphasizes the role of the natural conditions in allocating green landscape corridors.     

Identification of river water quality using the fuzzy synthetic evaluation approach.

Proper identification of water quality conditions in a river system based on limited observations is an essential task for meeting the goals of environmental management. Various classification methods have been used for estimating the changing status and usability of surface water in river basins. However, a discrepancy frequently arises from the lack of a clear distinction between each water utilisation mode, the uncertainty in the quality criteria employed and the vagueness or fuzziness embedded in the decision-making output values. Owing to inherent imprecision, difficulties always exist in some conventional methodologies when describing integrated water quality conditions with respect to various chemical constituents, biological aspects, nutrients, and aesthetic qualities. This paper presents a comparative study using three fuzzy synthetic evaluation techniques to assess water quality conditions in comparison to the outputs generated by conventional procedures such as the Water Quality Index (WQI). Based on a set of data collected at seven sampling stations, a case study for the Tseng-Wen River system in Taiwan was used to demonstrate their application potential. The findings clearly indicate that the techniques may successfully harmonise inherent discrepancies and interpret complex conditions. A further, newly developed fuzzy synthetic evaluation approach described in this paper might also be useful for verifying water quality conditions for the Total Maximum Daily Load (TMDL) program and be helpful for constructing an effective water quality management strategy.     

Design of fuzzy synthetic evaluation model for air quality assessment

Little attention was paid to growing air quality concerns until about a decade earlier in India. Indian Government started continuous monitoring of the urban air quality in Taj corridor area to protect the heritage monuments like Agra Fort, Fatehpur Sikri, the bird sanctuary at Bharatpur National Park and also the human health associated with air pollution. The aim of this study was to address air quality assessment using fuzzy synthetic evaluation model. The model was designed for four air pollutants (sulphur dioxide, nitrogen dioxide, suspended particulate matters and respirable suspended particulate matter). In the present paper, an approach is demonstrated for the determination of fuzzy air quality index by aggregating the four pollutants. The model also considers the weights of individual pollutants during aggregation. The weights of individual pollutants were determined using analytical hierarchical process. The model was applied for air quality assessment in four monitoring stations situated in Taj Trapezium Zone.