Landfill site selection by decision-making tools based on fuzzy multi-attribute decision-making method

Landfill site selection is a complex and time-consuming process, which requires evaluation of several factors where many different attributes are taken into account. Decision makers always have some difficulties in making the right decision in the multiple attribute environments. After identifying candidate sites, these sites should be ranked using decision-making methods. This study applies Chang’s fuzzy AHP-based multiple attribute decision-making (MADM) method for selection of the best site of landfills based on a set of decision criteria. The Fuzzy Analytic Hierarchy Process (FAHP) was designed to make pairwise comparisons of selected criteria by domain experts for assigning weights to the decision criteria. Analytic Hierarchy Process (AHP) is used to make pairwise comparisons and assign weights to the decision criteria. It is easier for a decision maker to describe a value for an alternative by using linguistic terms and fuzzy numbers. In the fuzzy-based AHP method, the rating of each alternative was described using the expression of triangular fuzzy membership functions. Once the global weights of the criteria is calculated by AHP, they are incorporated into the decision matrices composed by decision maker and passed to fuzzy-AHP method which is used to determine preference order of siting alternatives. In this study, a computer program based on the Chang’s fuzzy method was also developed in MATLAB environment for ranking and selecting the landfill site. As an example of the proposed methodology, four different hypothetical areas were chosen and implemented to demonstrate the effectiveness of the program. By using this program, the precision was improved in comparison with traditional methods and computational time required for ranking and selecting the suitable landfill site was significantly reduced.     

Using fuzzy TOPSIS method for mineral processing plant site selection

Site selection for the mineral processing is the most important decision made by owner that has a significant impact on the efficiency of the whole process. This is a critical decision which involves considering a number of criteria and finding the best location among feasible alternatives. Therefore, a multicriteria decision-making method is necessary to apply site-selection process to find the best location that meet desired conditions set by the selection criteria. This paper presents an application of TOPSIS method based on fuzzy sets (fuzzy TOPSIS), which is one of the broader multicriteria decision making means, used to select an appropriate site for mineral processing plant for Sangan iron ore mine (phase 2). For this purpose, at first considering the geological, technical, economical, and environmental factors, three feasible alternatives were selected for the processing plant using Geographical Information System. Then, based on the technical and experimental experiences and through judgment of the decision makers and experts, 14 criteria were established and these alternatives were evaluated. Finally, the alternatives were ranked and the best location was recommended.     

Site selection in municipal solid waste management with extended VIKOR method under fuzzy environment

Nowadays, selection of the suitable disposal site in municipal solid waste (MSW) management has become a challenge task for the municipal authorities, especially in fast-growing areas. Site selection can be viewed as a complicated multi-criteria decision-making (MCDM) problem requiring consideration of multiple alternative solutions and conflicting quantitative and qualitative criteria. In this paper, linguistic variables, which can be expressed as trapezoidal fuzzy numbers, are used to assess the ratings and weights for the selection criteria. The ordered weighted averaging operator is utilized to transform the fuzzy decision matrix into crisp values considering the decision maker’s attitudinal character. For selecting the best site, the extended VIsekriterijumska optimizacija i KOmpromisno Resenje (VIKOR) method is applied to determine the priority ranking of alternatives. As a result, a hierarchy MCDM model based on fuzzy set theory and VIKOR method is proposed to deal with the site selection problems in the MSW management system. An empirical study in Shanghai, China, is provided and comparison with the existing approach is conducted to illustrate the applicability and benefits of the proposed method.     

Application of fuzzy multi-attribute decision-making to select and to rank the post-mining land-use

The selection of an optimal reclamation method is one of the most important portions of the surface mining design. There are many factors in this problem which seriously influence decision-making. The fuzzy set theory was applied due to the effect of uncertain parameters involved in the decision-making process. Therefore, the fuzzy multi-attribute decision-making method was proposed. The aim of this study is to use the fuzzy technique for order preference by similarity to ideal solution method for ranking the optimal post-mining land-use and the fuzzy analytic hierarchy process method in order to determine the weights of each criterion. This approach is applied to the surface coal mine by employing 28 criteria which influence the decision-making procedure. The TOPSIS and AHP methods have been the most used methods of mining decision-making and demonstrated their ability to make critical decisions. By evaluating the alternatives and considering effective criteria with proposed methods, agriculture is the optimal post-mining land-use.     

Determination of earthquake-risky areas in Yalova City Center (Marmara region,Turkey) using GIS-based multicriteria decision-making techniques (analytical hierarchy process and technique for order preference by similarity to ideal solution)

Disaster mitigation as a pre-disaster measure within the scope of disaster risk management is significant in the sense of reducing the adverse effects of earthquakes in the context of earthquake-sensitive risk planning. In the urban planning context, the existence of numerous decision makers and alternatives, which are depending on many criteria, makes decision-making process difficult. This difficulty was overcomed through geographical information systems (GIS). In the context of GIS-based multicriteria decision-making (MCDM) analysis, we used analytic hierarchy process (AHP) and technique for order preference by similarity to ideal solution (TOPSIS) to determine earthquake-risky areas in Yalova City Center. First, AHP analysis related to geological and superstructure/infrastructure criteria was conducted and two separate AHP maps were obtained. Then, we conducted TOPSIS analysis to consider both criteria in the sense of earthquake risk-sensitive planning. Then, overall earthquake risk map obtained which could be used as an input for disaster mitigation processes.

     

Selection of wastewater treatment process based on the analytical hierarchy process and fuzzy analytical hierarchy process methods

This paper presents an application of the analytical hierarchy process and fuzzy analytical hierarchy process methods for selecting the best wastewater treatment process. The analytical hierarchy process is one of the best ways for deciding among the complex criteria structure in different levels, and the fuzzy analytical hierarchy process is a synthetic extension of the classical method when the fuzziness of the decision makers are considered. After reviewing aerobic treatment processes operated in Iran’s industrial estates and determining the main criteria used for treatment process evaluation, they are arranged in a hierarchy structure. Selection of the best wastewater treatment process is a multi-criteria decision making problem. Conventional methods are inadequate for dealing with the imprecise or vague nature of linguistic assessment. To overcome this difficulty, the fuzzy analytical hierarchy process is proposed for dealing with the vagueness of decision makers’ judgments. The alternatives consist of extended aeration, absorption bio-oxidation, integrated fixed-film activated sludge, sequencing batch reactor, aerated lagoon. Based on the general condition of industrial estate’s wastewater treatment plants, technical/administrative, economic and environmental criteria and their sub-criteria are weighted and then criteria evaluated and priorities of alternatives have been done by analytical hierarchy process and fuzzy analytical hierarchy process methods by the use of triangular fuzzy numbers. Finally, selection of the best process and ranking of these five processes are carried out by these foregoing methods, and some sensitivity analyses are conducted to show the results’ sensitiveness to the changes of the weights of the evaluation criteria.     

An extended fuzzy TOPSIS–GRA method based on different separation measures for green logistics service provider selection

In this paper, first, the criteria that make logistics service providers more “green” are determined as: cooperation with customer’s company and its customer, green government regulations, environmental management system, green process design, reduction in energy consumption and green network design. The criteria weights are determined by fuzzy AHP, based on expert opinions. Then, a new method is proposed, which is the combination of fuzzy TOPSIS and GRA, and used to evaluate green 3PLs based on different separation measures, as an extension, using trapezoidal fuzzy numbers. Five Turkish 3PLs serve in Istanbul are selected in order to apply a case study to show the applicability of the proposed method. Finally, the proposed method is verified with respect to different resolving coefficient values and separation measures and also compared with fuzzy TOPSIS and fuzzy VIKOR method results. Different multi-criteria decision-making methods can be applied and compared to check validity of our results for future studies. The proposed method can also be implemented to 3PLs in other countries.     

A new linguistic quantifier knowledge-guided OWA approach for mineral prospectivity mapping: a case study of the Bavanat Region,Iran

The main purpose of this study is to introduce a geographic information system (GIS)-based, multi-criteria decision analysis method for selection of favourable environments for Besshi-type volcanic-hosted massive sulphide (VHMS) deposits. The approach integrates two multi-criteria decision methods (analytical hierarchy process and ordered weighted averaging) and theory of fuzzy sets, within a GIS environment, to solve the problem of big suggested areas and missing known ore deposits in favourable environment maps for time and cost reduction. We doubled the fuzzy linguistic variables’ significance as a method to apply the arrange weights that the analytical hierarchy process (AHP)-ordered weighted averaging (OWA) hybrid procedure depends on. Another aim of this work is to assist mineral deposit exploration by modelling existing uncertainty in decision-making. Both AHP and fuzzy logic methods are knowledge-based, and they are affected by decision maker judgments. We used data-driven OWA approach in a hybrid method for solving this problem. We applied a new knowledge-guided OWA approach on data with changing linguistic variables according to the mineral system for VHMS deposits. Additionally, we used a vector-based method combination, which increased the precision of results. Results of knowledge-guided OWA showed that all of the mines and discovered deposits have been predicted with 100% accuracy in half of the size of the suggested area. To summarize, results improved the selection of possible target sites and increased the accuracy of results as well as reducing the time and cost, which will be used for field exploration. Finally, the hybrid methods with a knowledge-guided OWA approach have delivered more reliable results compared to exclusively knowledge-driven or data-driven methods. The study proved that expert knowledge and processed data (information) are critical important keys to exploration, and both of them should be applied in hybrid methods for reaching reliable results in mineral prospectivity mapping.     

An appropriate multiple criteria decision making method for solving electricity planning problems, addressing sustainability issue

In the past, decision making within the energy sector, especially in Iran, was limited to economic analysis. Lately, multiple criteria decision making has gained great popularity. However, this is not enough to make a right decision by considering sustainability. This paper deals with designing an appropriate multiple criteria decision making method to address the multifaceted nature of such problems. This task is the second precondition to make a decision which meets the sustainability criterion. This is done by revealing new facts about quantitative and qualitative data and the degree of compensation between the criteria. Moreover, this paper illustrates the capability of different methods with regard to sustainable energy planning and management in two steps: 1) comparison of two main approaches in the strategic energy planning context; 2) evaluation of multi attribute decision making methods and combining them. Combining four methods including Analytical hierarchy process, Preference ranking organization method for enrichment evaluation II, geometric mean and weighted sum seems to result in designing an appropriate method which meets the sustainability criterion. These contributions are proposed for comparing the renewable energy technologies with non-renewable ones. Nevertheless, these seem to be applicable in any comparison between discrete alternatives in the energy sector.     

Deriving preference order of post-mining land-uses through MLSA framework: application of an outranking technique

This study intends to take advantage of a previously developed framework for mined land suitability analysis (MLSA) consisted of economical, social, technical and mine site factors to achieve a partial and also a complete pre-order of feasible post-mining land-uses. Analysis by an outranking multi-attribute decision-making (MADM) technique, called PROMETHEE (preference ranking organization method for enrichment evaluation), was taken into consideration because of its clear advantages on the field of MLSA as compared with MADM ranking techniques. Application of the proposed approach on a mined land can be completed through some successive steps. First, performance of the MLSA attributes is scored locally by each individual decision maker (DM). Then the assigned performance scores are normalized and the deviation amplitudes of non-dominated alternatives are calculated. Weights of the attributes are calculated by another MADM technique namely, analytical hierarchy process (AHP) in a separate procedure. Using the Gaussian preference function beside the weights, the preference indexes of the land-use alternatives are obtained. Calculation of the outgoing and entering flows of the alternatives and one by one comparison of these values will lead to partial pre-order of them and calculation of the net flows, will lead to a ranked preference for each land-use. At the final step, utilizing the PROMETHEE group decision support system which incorporates judgments of all the DMs, a consensual ranking can be derived. In this paper, preference order of post-mining land-uses for a hypothetical mined land has been derived according to judgments of one DM to reveal applicability of the proposed approach.     

An interval matrix method used to optimize the decision matrix in AHP technique for land subsidence susceptibility mapping

The analytical hierarchy process (AHP) is one of the most effective methods for criteria ranking/weighting to have been successfully incorporated into GIS analyses. We present a new method for optimizing pairwise comparison decision-making matrices in AHP method, which has been developed on the basis of an interval pairwise comparison matrix (IPCM) derived from expert knowledge. The method has been used for criteria ranking in land subsidence susceptibility mapping (LSSM) as a practical test case, for which an interval matrix was generated by pairwise comparison. To compare the capability of the AHP method (a traditional approach) with that of the proposed IPCM method (a novel approach), 11 creations of LSSM were ranked using each approach in turn. The criteria weightings obtained were then used to produce LSSM maps based on each of these approaches. The results were tested against a data set of known land subsidence occurrences, indicating an improvement in accuracy of about 14% in the LSSM map that was developed using the IPCM method. This improvement was achieved by minimizing the uncertainty associated with criteria ranking/weighting in a traditional AHP and could form a basis for future research into minimizing the uncertainty in weightings derived using the AHP method. Our results will be of considerable importance for researchers involved in GIS-based multi-criteria decision analysis (MCDA) and those dealing with GIS-based spatial decision-making methods.     

Risk identification on hydropower project using the IAHP and extension of TOPSIS methods under interval-valued fuzzy environment

Risk identification on hydropower project, the first step of risk management process, is an extremely complex issue and has a significant impact on the efficiency of the following risk assessment and control. On the other hand, finding out some more possible risk factors among many risk ones is a multi-criteria decision making problem. This paper develops an evaluation model based on the interval analytic hierarchy process (IAHP) and extension of technique for order preference by similarity to ideal solution (TOPSIS), to identify exactly the more possible risk factors under a complex and fuzzy environment. In this paper, the IAHP is used to analyze the structure of risk identification problems in hydropower project and to determine weights of the criteria and decision makers, and extension of TOPSIS method with interval data is used to obtain final ranking of potential risk factors in hydropower project. Risk identification on an earth dam is conducted to illustrate the utilization of the model proposed in this paper. The application could be interpreted as demonstrating the effectiveness and feasibility of the proposed model.     

基坑支护方案的灰色模糊可变决策模型

针对影响基坑支护方案决策因素所具有的不确定性、模糊性以及影响因素与评价指标间的相互关联性特点,基于灰色理论和模糊数学理论,建立了基坑支护方案的灰色模糊可变决策模型。应用基于贴近度最大的组合赋权方法确定评价指标权重,并用集值统计法对定性指标进行量化,以解决影响模型决策结果准确程度的关键问题。工程实例分析表明,采用该模型更为科学、有效,易于实现程序化。更重要的是,该方法能够提高优选决策的合理性和可信度,为决策者提供有力的参考,具有一定推广和应用价值。     

TISS: a decision framework for tailing impoundment site selection

Tailing dam is one of the most important mining operations interface with surrounding environment even as long as many years after ore reserve exhausted. Therefore, appropriate design and management respect to future limitations of environmental regulations is required. Recently, effect of multiple criteria on tailing impoundment site selection makes it complex as the conventional procedures unable to answer. The systematic approach of multi attribute decision-making helps decision-makers select the most preferable decision and provide the basis of a decision support system. This paper developed new strategy based on fuzzy multi attribute group decision-making methods including: technique for order preference by similarity to ideal solution and analytical hierarchy process in fuzzy group environment. A hypothetical case is processed to demonstrate the strategy’s efficiency and results are compared and ranked so that the most preferable option is identified.     

层次分析法在致密油有利区优选中的应用——以川中侏罗系大安寨段为例

层次分析法常用于解决复杂系统分析与决策中目标优选、排序等问题,也适用于油气勘探领域。在前人致密油地质特征研究的基础上,总结了致密油有利区优选指标。使用层次分析法优选有利区的核心内容是建立层次结构模型和构建2类矩阵。以四川盆地中部侏罗系大安寨段为例,介绍了使用层次分析法优选有利区5个主要步骤:1根据研究区地质特征,确定目标及方案,构建目标层和方案层;2根据影响致密油富集的要素,确定准则层;3构建准则层中各要素的成对比较矩阵,确定各准则要素的相对权重;4构建各准则要素对不同方案的判断矩阵,确定不同方案中各准则要素的权重;5将不同方案各准则要素的权重矩阵与准则要素的相对权重矩阵相乘,得到各方案的层次排序,进而选出最佳方案。优选的川中侏罗系大安寨段致密油最有利勘探区为金华—莲池区。操作简单、不需考虑下限值、适用范围广是层次分析法优选有利区的优点,但由于层次分析中的标度根据人为经验赋值,不同评价人员给出的评价结果有所不同。将层次分析法与GIS、特尔菲法、模糊数学法相结合,可以提高准则要素的优选合理性及赋值准确性。     

Probabilistic Fuzzy Logic Modeling: Quantifying Uncertainty of Mineral Prospectivity Models Using Monte Carlo Simulations

Significant uncertainties are associated with the definition of both the exploration targeting criteria and computational algorithms used to generate mineral prospectivity maps. In prospectivity modeling, the input and computational uncertainties are generally made implicit, by making a series of best-guess or best-fit decisions, on the basis of incomplete and imprecise information. The individual uncertainties are then compounded and propagated into the final prospectivity map as an implicit combined uncertainty which is impossible to directly analyze and use for decision making. This paper proposes a new approach to explicitly define uncertainties of individual targeting criteria and propagate them through a computational algorithm to evaluate the combined uncertainty of a prospectivity map. Applied to fuzzy logic prospectivity models, this approach involves replacing point estimates of fuzzy membership values by statistical distributions deemed representative of likely variability of the corresponding fuzzy membership values. Uncertainty is then propagated through a fuzzy logic inference system by applying Monte Carlo simulations. A final prospectivity map is represented by a grid of statistical distributions of fuzzy prospectivity. Such modeling of uncertainty in prospectivity analyses allows better definition of exploration target quality, as understanding of uncertainty is consistently captured, propagated and visualized in a transparent manner. The explicit uncertainty information of prospectivity maps can support further risk analysis and decision making. The proposed probabilistic fuzzy logic approach can be used in any area of geosciences to model uncertainty of complex fuzzy systems.     

Evaluation of soil collapse potential in regional scale

Collapsible soils have considerable strength and stiffness in their dry natural state but settle dramatically when they become wet. This paper documents a low-cost, qualitative evaluation scheme using fuzzy set analysis to determine site collapsibility based on subjective knowledge of the geological, geotechnical, and environmental conditions and their uncertainty. For each category, factors or subcategories were defined in a decision tree based on relevant literature. Each category and subcategory was then weighted or rated using linguistic terms developed from expert assessment. The linguistic data or information obtained from the assessments was represented and processed using fuzzy sets. To calibrate the criteria, 87 collapse potential tests were performed on undisturbed soil samples gathered from 27 different locations throughout Iran, leading to the definition of a standard collapse potential fuzzy set. Finally, on the basis of the established criteria, a collapse potential map was prepared for a suburban area in the western part of the city of Kerman, Iran.     

Nature of occurrence of phosphatic bands in Owk Formation,Neoproterozoic Kurnool basin,Andhra Pradesh

Rock slope instabilities are a major hazard for human activities often causing economic losses, property damages and maintenance costs, as well as injuries or fatalities. For slope stability analysis of open pit mines, series of studies must be carried out in order to identify the criteria which should take into consideration. In this research geotechnical parameters; Geological Strength Index (GSI), Rock Quality Designation (RQD), Cohesion (C), angle of internal friction (φ), uniaxial compressive strength (UCS) and Rock mass deformation modulus (E_m) which are obtained from data measured within geotechnical boreholes and pore pressure (U) are considered as the criteria to evaluate stability of pit No.1 of the Gole Gohar iron mine, located in Kerman province, south east of Iran. Since human judgments and preferences are often vague and complex and decision makers cannot estimate their preferences with an exact scale, we can only give linguistic assessments instead of exact ones. So fuzzy set theory introduced into Analytical Hierarchy Process (AHP). Fuzzy AHP (FAHP) is put forward to solve such uncertain problems. In this paper, FAHP method is used to determine the weights of the criteria by decision makers and then classification of the stability of blocks are determined by TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) method by the shortest distance to positive ideal solution (PIS) and the longest distance to negative ideal solution (NIS).     

A decision support system using analytical hierarchy process (AHP) for the optimal environmental reclamation of an open-pit mine

The selection of an optimal reclamation method is one of the most important factors in open-pit design and production planning. It also affects economic considerations in open-pit design as a function of plan location and depth. Furthermore, the selection is a complex multi-person, multi-criteria decision problem. The group decision-making process can be improved by applying a systematic and logical approach to assess the priorities based on the inputs of several specialists from different functional areas within the mine company. The analytical hierarchy process (AHP) can be very useful in involving several decision makers with different conflicting objectives to arrive at a consensus decision. In this paper, the selection of an optimal reclamation method using an AHP-based model was evaluated for coal production in an open-pit coal mine located at Seyitomer region in Turkey. The use of the proposed model indicates that it can be applied to improve the group decision making in selecting a reclamation method that satisfies optimal specifications. Also, it is found that the decision process is systematic and using the proposed model can reduce the time taken to select a optimal method.     

Ranking desertification indicators using TOPSIS algorithm

Desertification is the result of natural and anthropogenic processes, leading to degradation or loss of the land’s productivity and complexity. To assess the desertification status, integrated set of indicators must be identified. Indicators must provide synthetic information on threshold levels, status and evolution of relevant physical, chemical, biological and anthropogenic processes. Multi-criteria decision-making (MCDM) is a collection of methodologies to compare, select, or rank multiple alternatives that involve incommensurate attributes. Technique for order preference by similarity to ideal solution (TOPSIS) method is a multiple criteria method to identify solutions from a finite set. TOPSIS is an algorithm for determining the most preferable choices among the possible indicators that can be developed. The aim of this paper is to introduce TOPSIS as a decision-making method for the selection and integration of desertification indicators. The simulation case study presented here is related to the selection of the best set of indicators to monitor land degradation by remote sensing in three different countries (Brazil, Mozambique and Portugal), within the framework defined by the DesertWatch Extension project.