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Given its widespread potential and technological advancements, it is critical to use the greatest amount of wind power in reaching the 100% renewable energy target in power grids. SWOT (Strengths, Weaknesses, Opportunities, and Threats) analysis is frequently used to evaluate alternative strategies in multi-criteria decision issues. This paper employs a hybrid Fuzzy Analytic Network Process (FANP) approach based on SWOT to assess the future development of wind power capacities in Turkey in light of the sectoral effects of the Covid-19 outbreak in 2020. To validate the proposed approach, the results are compared to the results of the SWOT-based Analytic Network Process (ANP), Analytic Hierarchy Process (AHP), and fuzzy AHP (FAHP). According to the findings, "Development of domestic and efficient technologies (ST1)" and "Sustaining support mechanisms in investments and technological research (SO2)" are the best alternative strategies in all analysis models. While the priority ranks of other alternative strategies are the same in AHP and FAHP hierarchical techniques, FANP differs from ANP when the linguistic assessment process is taken into account. This study proposes long-term strategies for increasing wind power capacity and sector sustainability, and it demonstrates that FANP could be an appropriate approach for prioritizing these strategies in current scenarios. [ABSTRACT FROM AUTHOR]

Multi-criteria decision making (MCDM) methods have become increasingly popular in site selection decision-making of renewable energy power plants because they consider multiple conflicting goals and decision-maker preferences. In this paper, a systematic literature review of MCDM applications for renewable energy site selection is performed, covering a total of 85 papers published from 2001 to 2018 in high-level journals (chosen from the ScienceDirect database). This paper has summarized the exclusion criteria and evaluation criteria of site selection for five energy sources. The five site selection stages, criteria selection, data normalization, criteria weighting, alternative evaluation and result validation, are revealed by content analysis. All papers are further classified by the date, energy source, journal of publication, country of author affiliation, and study area. It is found that different energy sources emphasize different criteria; however, some similarities exist. Literature surveys and expert opinions are most common criteria selection method. Reclassification is most frequently used data normalization method. The analytic hierarchy process is popular for weighting. In alternative evaluation, geographic information systems and weighted linear combination are the most popular tools. Varying the criteria weights is most commonly used result validation method. • This is the first review of MCDM applications for renewable energy site selection. • It covers five energy sources: solar, onshore wind, offshore wind, wave and tidal. • It focuses on two types of criteria and methods in the five site selection stages. • It also involves methods for data normalization and result validation. • The combination of GISs and MCDM is the most popular tool in this research area. [ABSTRACT FROM AUTHOR]

The analytic hierarchy process (AHP) is usually employed to evaluate complex decisions, in which the assigned weights are specified artificially. In response, neural networks instead of manual selections can be used to optimize the assigned weights to avoid subjective errors. However, traditional neural networks usually suffer local extremums and cannot extract the deep features in the data. At the same time, variables that do not necessarily participate in the evaluation will also affect the results. In this context, a novel deep residual network based analytic hierarchy process which integrates principal component analysis algorithm (PIDRN-AHP) is suggested in this paper. Firstly, the operation variables most related to the target variables are extracted as the input data by principal component analysis (PCA) method. By fitting the residuals between input data and mapped output data with multiple continuous stacked non-linear computational layers, a deep residuals network is constructed with residual block local depth neural network structure units. Taking advantage of the deep network, the PIDRN-AHP can achieve optimal solutions of AHP global weights, avoid subjective errors and avoid possible gradient disappearance of deep networks due to the layer increase. The proposed method is applied to operational evaluations of Tennessee Eastman Process (TEP). Compared with the traditional AHP, BP-AHP and DRN-AHP experiments show that the PIDRN-AHP can achieve the most satisfied performances. • A novel evaluation method called PIDRN-AHP is proposed in this paper. • The dimensionality and complexity of the calculation will be reduced with PCA layer. • Multiple continuous stacked non-linear computational layers are used to fit the residuals. • The possible gradient disappearance of deep network model can be avoided. • Application results confirm the effectiveness and reliability of the proposed method. [ABSTRACT FROM AUTHOR]

• Choosing a landfill location is a complex process. • Many influential factors must be assessed and evaluated. • The factors could be physical, environmental, social, or economical. • Multi Criteria Decision Making (MCDM) can help the decision making process. • With enough time and resources, Fuzzy Analytical Network Process is most effective. Although a lot of research has focused on energy recovery and recycling of valuable materials from wastes to reduce loads on landfills, landfilling is still an inseparable part of solid waste management. Since landfills potentially pose a risk to human health and the surrounding environment, landfill site selection is an important endeavor that has to be carried out with great care. Choosing a suitable location for landfills depends on several factors and is a complicated procedure. In this paper, a comprehensive review of landfill site selection methods, with an emphasis on multi criteria decision making (multiple criteria decision analysis) has been presented. Assessments indicate that the most frequently used methods are weighted linear combination (WLC), ordered weighted averaging (OWA), analytic hierarchy process (AHP), fuzzy analytic hierarchy process (F-AHP), TODIM, fuzzy TODIM, analytic network process (ANP), fuzzy-analytic network process (F-ANP), and grey systems theory, each of which is discussed. The most widely used factors for selecting a landfill site are groundwater depth, surface water vicinity, elevation, land slope, soil permeability, soil stability, flooding susceptibility, lithology and stratification, faults, land use type, nearby settlements and urbanization, cultural and protected site vicinity, wind direction, roads, railways, proximity to building materials, pipelines and powerlines, and proximity to airports. Image, graphical abstract [ABSTRACT FROM AUTHOR]

This paper presents an integrated Fuzzy Analytical Hierarchy Process (f AHP) and Weighted Fuzzy Axiomatic Design (wf AD) methodology for a strategic level problem of hydrogen energy storage (HES) method selection for Turkey. Considering alternatives of tank, metal hydride and chemical storage, we design our decision problem with respect to five assessment criteria as weight, capacity, storage loss and leak, reliability, and total system cost. In the solution methodology, we first implement f AHP to determine criteria weights by incorporating linguistic judgement and vague information. Next, we define functional requirements and design parameters for the selection problem and use wf AD to compare alternatives. After implementing the proposed integrated approach, we perform additional sensitivity analysis experiments to test the robustness of the solution with respect to changes in functional requirements. • We consider a hydrogen energy storage method selection problem for Turkey. • We incorporate three alternatives as tank, metal hydride, and chemical. • We use fuzzy analytical hierarchy process to determine criteria weights. • We use weighted fuzzy axiomatic design to select the most appropriate alternative. • Our results reveal that metal hydride is the most appropriate solution. [ABSTRACT FROM AUTHOR]

• The Comprehensive Evaluation Method base on DHGF was built to locate the substation. • Evaluation index system was constructed for substation location. • Better substation site was selected from two similar candidates. By now, there is little research on evaluation of the tow similar candidate sites for the selection substation's location. To improve this problem, in this paper, the comprehensive evaluation method based on the Delphi, analytic Hierarchy process, Gray relations analysis and Fuzzy integrated evaluation (DHGF) was newly selected to choose the substation's location. To build the evaluation system, Grid structure, Economic performance and External environment as the main influences and thirteen indexes were selected, and the comprehensive evaluation approach based on DHGF was established. The address selection of a 220 kV substation in the east of Xianxian county was studied by the method. At first, we graded the two similar candidate sites by Delphi approach, then the analytic hierarchy process was used to obtain the combined weights, at last the GF model was used to evaluate the two candidate schemes. Based on the DHGF comprehensive evaluation method, we selected the better location for the 220 kV substation from two similar candidate sites. The results showed that the comprehensive evaluation method based on DHGF can be used to choose the location of substation from the tow similar candidate sites. From this case, the effectiveness of the evaluation method based on DHGF to locate the substation was verified. [ABSTRACT FROM AUTHOR]

It is now well established that solar energy is a reliable alternative way to reduce greenhouse gas emissions and to mitigate climate change effects. In Morocco, solar energy investments are rapidly rising since 2009 and are expected to grow dramatically in the next decade. Site selection is a critical issue when large-scale solar plants are being planned. In this paper, the multi-criteria evaluation method is used to identify suitable sites to host Photovoltaic projects in southern Morocco. For this purpose, geographical information systems and analytic hierarchy process methods were combined to represent a high-resolution map that compares the potential of the studied region to host large-scale Photovoltaic projects. HOMER software was then used for modeling and simulating a 10 MW grid-connected PV system. The optimum scheme is analyzed to assess the economic feasibility in the most suitable site in the Souss-Massa region. The findings from this study confirm that 24.08% of the studied area offers suitable sites to host the Photovoltaic farms. The HOMER simulation has clearly shown that the grid-connected Photovoltaic system is beneficial in the long run, although its initial capital is higher than the grid supply only. Also, the cost of electricity generated from Photovoltaic panels is affordable. • Geographical information system based Multi-Criteria Decision analysis was applied. • An analytical hierarchy process is used to assign weights to the criteria. • 24% of the total surface area of the region is suitable for solar farms. • HOMER was used to analyze the feasibility of 10 MW photovoltaic grid-connected. [ABSTRACT FROM AUTHOR]

Abstract: In this paper the AHP (Analytic Hierarchy Process) and the ANP (Analytic Network Process) are applied to help the managing board of an important Spanish solar power investment company to decide whether to invest in a particular solar-thermal power plant project and, if so, to determine the order of priority of the projects in the company's portfolio. Project management goes through a long process, from obtaining the required construction permits and authorizations, negotiating with different stakeholders, complying with complex legal regulations, to solving the technical problems associated with plant construction and distribution of the energy generated. The whole process involves high engineering costs. The decision approach proposed in this paper consists of three phases. In the first two phases, the managing board must decide whether to accept or reject a project according to a set of criteria previously identified by the technical team. The third phase consists of establishing a priority order among the projects that have proven to be economically profitable based on project risk levels and execution time delays. This work analyzes the criteria that should be taken into account to accept or reject proposals for investment, as well as the risks used to prioritize some projects over others. [Copyright &y& Elsevier]

Environmental management, being an important component in strategies for achieving sustainable development of processes and products, has emerged as a proactive approach in majority of the manufacturing organizations. From the strategic perspective environmentally conscious manufacturing (ECM) programs lead to better environmental management practice. The objective of the current paper is to present an integrated and holistic framework to evaluate ECM programs. This framework combines three multi-criteria decision analysis (MCDA) methods to consider eight major environmentally conscious manufacturing indicators (ECMI) in order to identify the efficiency of each ECM program. First the interdependence relationship among the ECMIs is established using decision-making trail and evaluation laboratory (DEMATEL). Then a range of weightage (i.e. upper and lower bounds) is created for each ECMI using analytic network process (ANP) to include managerial preferences. Finally, this range of weightage for each indicator is applied to perform restricted multiplier data envelopment analysis (RMDEA). Results show that the technical efficiency of the inefficient ECM programs for integrated RMDEA, on average, is calculated as 53.2% whereas traditional input oriented DEA provides the same score as 72.3%. This clearly indicates that integrated RMDEA is better than the input oriented DEA because same level of output could be produced with lesser resources if the ECM programs perform on the frontier. Hence, the advantage of this methodology is that the managerial preferences are successfully implemented through this newly developed hybrid methodology that will help to reduce less resource consumption and lead to better environmental policy. [ABSTRACT FROM AUTHOR]

This paper aims to determine the suitable places for a radioactive waste repository in Peninsular Malaysia to implement a permanent disposal facility for disposal sealed radioactive sources (DSRS). The sole Malaysia interim waste storage that stores a large proportion of DSRS was expected to be occupied by 2025 fully. Currently, the nation's licensing board promoted the borehole disposal facility to resolve the full capacity dilemma. The potential sites were determined by the geographical information system (GIS) based Weight Linear Combination (WLC) analysis, integrating the improved Analysis Hierarchical Process (improved AHP) and the technique for order of preference by similarity to ideal solution (TOPSIS) approaches. The sensitivity analysis was applied to identify the main contributing factors for corresponding Peninsular Malaysia selection. Ten parametric criteria and three exclusion criteria are applied to assess the potential areas and screen out the unfavorable regions, respectively. Results indicated the final composite map presents 435 areas of very high suitability class with 17.5% coverage from the total suitability class. The top 5 largest candidates with high potentiality are Jerantut & Ulu Lepar, Bandar Tun Razak, Pertang & Simpang, Pertang, Tanjung Ipoh, and Labis, where come from three provinces: Pahang, Negeri Sembilan and Johor. By TOPSIS model, the ranks for these five candidates are Jerantut & Ulu Lepar, Bandar Tun Razak, Tanjung Ipoh, Labis and Simpang Pertang. The model revealed that the suitability ranks is proportional to its area sizes in the approximate values of criteria. The three main contributing factors in Peninsular Malaysia are hydrogeology, seismicity and lithology, which are strongly recommended to involve in other corresponding site selection project. • Top five candidates for radioactive waste disposal site in Malaysia are Jerantut & Ulu Lepar, Bandar Tun Razak, Tanjung Ipoh, Labis and Simpang Pertang. • Three main contributing factors for site selection in Malaysia are hydrogeology, seismicity and lithology. • The suitability index rank is proportional to the area sizes in the consideration of area factor. [ABSTRACT FROM AUTHOR]

• An improved thermal-hydraulic-mechanical coupling model was established. • Evaluation index system for geothermal energy development effect was put forward. • Evaluation method for EGS based on AHP and FCE was proposed. • Well arrangement patter and development parameters were optimized. In the paper, the thermal-hydraulic-mechanical (THM) coupling model is improved by considering more factors, and a comprehensive evaluation method is proposed to optimize the heat extraction way. The thermal extraction characteristics in the Enhanced Geothermal System (EGS) and their influence factors were modeled by several researchers, and various evaluation and optimization methods were established. However, by comparing various thermal-hydraulic-mechanical (THM) models, we find that these factors of THM models are not considered comprehensively, and current EGS evaluation focuses on the individual index, the multi-objective evaluation index system of EGS has not been proposed, and a comprehensive evaluation system considering multiple indexes has not been established yet. In this study, a thermal-hydraulic-mechanical coupling model, considering matrix, fractures and changes in physical parameters of rock and fluid, was established for optimizing the EGS. The evaluation index system, including the operation life, the thermal breakthrough time, the average heat production rate, the total heat recovery factor and the re-injection factor, were presented. And the comprehensive optimization method based on analytic hierarchy process (AHP) and fuzzy comprehensive evaluation (FCE) of EGS were proposed. The model is verified by two analytical solutions. Moreover, the model was solved by finite element method (FEM) to optimize various programs of developing the EGS. In this paper, the performances of different geothermal extraction methods are compared and the different extraction parameters are optimized. The results show that the optimized geothermal mining method has better effect than that before optimization. The orthogonal test shows the optimal case of 5 fractures, the fracture permeability of 10D, the well spacing is 400 m and the production pressure draw-down of 20 MPa. The research results provide an accurate and effective method to optimize the development mode of geothermal resources, which is conductive to improve the geothermal energy efficiency. [ABSTRACT FROM AUTHOR]

The European spruce bark beetle ' Ips typographus L.' is the most serious disturbance agent for European forests. The complex interactions of many influencing factors need to be integrated into a model-based decision-support system to reduce the potential loss of forests. This paper compares two methodological approaches for spatially-explicit prediction of the predisposition for bark beetle infestations. The fuzzy analytic hierarchy process and the Bayesian belief networks were used in combination with a geographical information system to manage uncertainties. Using available data resources, the two approaches were evaluated to produce robust results for forest practitioners and to support measures to minimize the spread of bark beetles. The findings revealed that nearly 32% of the sites investigated in a case study were moderately-high or high risk categories. It is concluded that BBN is more efficient. Both methods can easily be used to analyze environmental problems involving complex interactions among various criteria. [Display omitted] • Comparison of the application of spatial BBN and fuzzy-AHP in forest ecology. • Spatially explicit evaluation of the predisposition of bark beetle infestation. • Participatory process to quantify expert and stakeholder perceptions. • BBN approach more efficient than fuzzy-AHP. [ABSTRACT FROM AUTHOR]

• Applying the MCDM process for MUT location selection based on spatial data. • Defining the criteria that influence the MUT location selection. • Defining the required GIS datasets for quantifying the score of each street segment. • Comparing the ranking results AHP and ANP combined with TOPSIS. • Developing a prototype system to integrate the MCDM methods in a GIS platform. Multi-purpose utility tunnels (MUTs) integrate all underground utilities in one accessible tunnel. MUTs reduce the need for excavations and their associated costs, as well as the resulting traffic congestion. Several MUTs have been implemented in different parts of the world. Their locations have either been politically influenced or selected to preserve heritage sites or to meet the conditions of a newly developed city. Nevertheless, selecting the location in an existing city under street segments is affected by several criteria that have different spatial characteristics. Combining these characteristics and managing the trade-offs that exist between them determine the ranking of alternative MUT locations. The use of subjective and objective weights in the decision-making process will offer different perspectives from the decision-maker's perspective and the data itself, respectively. This paper aims to analyze spatial data as an input in the multi-criteria decision-making (MCDM) process of the MUT location selection. The objectives are: (1) defining the criteria that influence the MUT location selection, (2) defining the required GIS datasets for quantifying the criteria as scores for each candidate street segment, (3) analyzing the impacts of the dependencies between the criteria by comparing the ranking results of two MCDM methods (i.e., Analytic Hierarchy Process (AHP) and Analytic Network Process (ANP)) combined with the Technique for Order Preference by the Similarity to Ideal Solution (TOPSIS), (4) analyzing the difference between using subjective weights or objective weights, and (5) developing a prototype system to integrate the MCDM methods in a GIS platform. A vector-based spatial analysis is conducted to identify the suitable locations for MUT construction based on 12 criteria representing physical condition information or affecting social costs. Two subjective MCDM methods (i.e., AHP and ANP) are used to generate each criterion's weights, and the ranking of alternatives is determined using TOPSIS. Another set of weights representing the objective weights are calculated for each criterion using the Shannon Entropy method. These weights are combined with TOPSIS to obtain an objective ranking of the alternatives. Based on the results from the different combinations (AHP + TOPSIS, ANP + TOPSIS, and ENTROPY + TOPSIS), the top alternative is always the same. [ABSTRACT FROM AUTHOR]

Through exploring driver's lane-changing decision mechanism, we divide the lane-changing decision-making process into two stages, i.e. lane-changing motivation and lane-changing decision. The influence attributes of decision-making are classified into two categories, i.e. internal decision attributes and external decision attributes. This paper presents a multi-attribute lane-changing decision model based on analytic hierarchy process after above work, introduces a newly-modified multilane traffic cellular automata model. By means of the numerical simulation under different traffic densities with various lane-line-markings as the external decision attributes the obtained conclusions show that, of a vehicle in system at each update time-step, the average lane-changing motivation probability is related directly to the internal decision attributes and the average lane-changing success probability is depend on both of internal and external decision attributes, the distribution of the lane-changing motivation probabilities and the lane-changing success probabilities fully response the variations of lane-line-marking. By and large, the proposed model has ability to analysis the legal implication of each pattern of lane-line-marking set in this paper. Due to the excellent expansibility of analytic hierarchy process frame structure, it should be improved to deal with more external decision attributes synchronously in future research. • The lane-changing(LC) decision process is divided into motivation and decision. • A LC decision model based on Analytic Hierarchy Process (AHP) is constructed. • This LC model embed in cellular automata can describe more decision attributes. [ABSTRACT FROM AUTHOR]

Energy efficiency analysis and production efficiency improvement are effective ways to promote the sustainable and stable development of ethylene industries. Therefore, this paper proposes novel data envelopment analysis cross-model integrated interpretative structural model and analytic hierarchy process for energy efficiency evaluation and optimization modeling. The interpretative structural model integrating analytic hierarchy process is used to fuse the multidimensional production data to reduce the dimension and obtain comprehensive evaluation indicators, thus reducing the multidimensional indicators influence on the data envelopment analysis model. Then these several fusion results are used as the input indicators of the improved data envelopment analysis cross-model. And the ethylene yield is used as the output index to build the energy efficiency evaluation and optimization model of ethylene production plants. Finally, according to cross-efficiency values and slack variables, the energy efficiency levels of ethylene plants in each month and year are analyzed. The experimental results show that the distinction of the efficiency values is more obvious and accurate. Moreover, the proposed method can optimize production efficiency and improve the proportion of the efficiency value greater than 0.8 increased by 66.6% of ineffective production plants. Image 10547 • A novel DEACM integrated ISM-AHP method is proposed. • Energy efficiency evaluation and optimization model is obtained. • The distinction of the efficiency values is more obvious and accurate. • The proportion of ineffective production plants is increased by 66.6%. [ABSTRACT FROM AUTHOR]

In this paper, we propose a novel hybrid multiple attribute decision-making (MADM) approach, which includes fuzzy analytic hierarchy process (fuzzy AHP) and gray multi-objective optimization by ratio analysis (MOORA-G). By using fuzzy and gray numbers, we successfully deal with the qualitative and uncertain inputs that often arise from real-world decision-making process. We adopt this hybrid approach to take the advantages offered by both methods, and designate the former for weighting the considered criteria, and the latter for ranking the alternatives. To demonstrate the performance of the proposed hybrid approach, we apply it to a case study on the selection of third-party reverse logistics providers (3PRLPs) for a car parts manufacturing company and benchmark it with the MOORA method. The outcome of this study indicates that our proposed approach can offer more viable performance when facing qualitative data and input uncertainties, and consequently, lends itself to a wider range of applications. [ABSTRACT FROM AUTHOR]

• A hybrid constrained fuzzy, AHP and stochastic model is proposed. • The proposed method is applied to a selection problem in mineral processing. • The method results in less uncertainty than existing AHP and fuzzy AHP methods. • The effect of the number of decision makers on rank discrimination is examined. • This is the first study that analyses rank reversal for fuzzy AHP methods. The ability of the analytical hierarchy process (AHP) when applied to the choice problem in the context of group decision making under uncertainty has been often criticised. AHP is not able to fully capture the various opinions and the uncertainty associated with the lack of information. This work develops an integrated constrained fuzzy stochastic analytic hierarchy process (IC-FSAHP) method in order to deal with the aforementioned drawbacks. IC-FSAHP combines two existing fuzzy AHP (FAHP) methods and further extends its applicability by implementing stochastic simulations. A case study has been conducted in order to assess the ability of IC-FSAHP; the results showed that IC-FSAHP is able to capture the uncertainty and multiple DMs' opinions. This paper also discusses the effect that the number of DMs has in enhancing rank discrimination. Besides, the possibility of the occurrence of rank reversal because of the use of IC-FSAHP has been analysed. The results showed that the ranking of alternatives was preserved throughout the changes in the number of alternatives, however, rank reversal occurred in the case of changes in judgements scales. By comparing the U-uncertainty in fuzzy global priorities obtained using IC-FSAHP to that obtained using an existing FSAHP method, we show that our method is capable of minimising the risk of losing important knowledge during the computations. We also discuss how IC-FSAHP can decrease the uncertainty and increase the reliability of the decisions by means of robust computations. [ABSTRACT FROM AUTHOR]