Fuzzy Decision-making Approach Research Articles

Sustainable risk management strategy selection using a fuzzy multi-criteria decision approach

While several studies focused on the evaluation of risk management strategies to select the sustainable ones using multi-criteria analysis, most of these studies did not necessarily dealt with the integration of uncertainties. In a context where uncertainties are inherent to natural hazards management decision-making process, the challenge is to systematically take uncertainties into account throughout the assessment process in order to avoid biased decisions. This paper attempts to tackle this challenge by suggesting a methodological approach based on the application of fuzzy multi-criteria decision-making methods. Uncertainties are addressed in two main ways. First, fuzzy AHP is used to estimate the importance of each of the evaluation criteria. Then, fuzzy weighted arithmetic mean method or fuzzy PROMETHEE are used to prioritize the strategies regarding the set of criteria, considering a compensatory or non-compensatory reasoning in order to derive final ranking. This approach is tested in a case study proposing sensitivity analysis in order to study the impact of the compensation phenomenon and the integration of uncertainty in the choice of a sustainable risk management strategy. This hybrid fuzzy multi-criteria decision approach provides a structured framework for identifying the most sustainable strategy under uncertainty.

Allocation of FACTS Devices Using a Probabilistic Multi-Objective Approach Incorporating Various Sources of Uncertainty and Dynamic Line Rating

Flexible AC transmission system (FACTS) controller play an essential role in increasing the penetration level of renewable energy resources owing to their ability in continuously controlling the active and reactive power flow in the network. This paper presents a probabilistic multi-objective optimization approach to obtain the optimal sizes and locations of static var compensators (SVCs) and thyristor-controlled series capacitors (TCSCs) in a power transmission network with high penetration level of wind generation. The objective of the problem is to maximize the system loadability while minimizing the network power losses and the installation cost of the FACTS controllers. In this study, the uncertainties associated with wind power generation and the correlated load demand are considered. The uncertainties are handled in this work using the points estimation method. Moreover, the dynamic line ratings (DLRs) of the transmission lines are considered in this work. In this case, the maximum transmission capacity of transmission lines is estimated dynamically according to the weather conditions. Considering the DLRs or transmission lines is expected to avoid unrealistic congestion in the network, and hence, improve its loadability. The optimization problem is solved using the multi-objective teaching-learning based optimization (MO-TLBO) algorithm to find the best locations and ratings for the FACTS controllers. Additionally, a technique based on the fuzzy decision-making approach is employed to extract one of the Pareto optimal solutions as the best compromise. The proposed approach is applied on the modified IEEE 30-bus system. The numerical results demonstrate the effectiveness of the proposed approach and show that the maximum loadability limit of the study system increases when considering the DLR. This limit can be enhanced to 123.0% without FACTS controller and 137.0 %,130 % and 132.0% by SVC, TCSC and (SVC-TCSC) respectively.

Evaluating Recognitive Balanced Scorecard-Based Quality Improvement Strategies of Energy Investments With the Integrated Hesitant 2-Tuple Interval-Valued Pythagorean Fuzzy Decision-Making Approach to QFD

This study aims to identify quality improvement strategies for energy investments. For this purpose, a model is proposed which includes 4 different stages. In the first stage, the MCDM problem is identified for evaluating the service development for energy industry. In this framework, quality function deployment (QFD) approach is taken into consideration which includes both customer expectations and technical requirements at the same time to improve the quality in the organization. The second stage is related to the calculation of the correlation coefficients of decision matrices for the criteria by considering hesitant 2-tuple interval-valued Pythagorean fuzzy sets. The third stage includes the weighting of the customer expectations with hesitant 2-tuple interval-valued Pythagorean fuzzy (HIVPF) DEMATEL. In the final stage, TRIZ-based quality improvement strategies of energy investments are ranked by using 2-tuple HIVPF TOPSIS. Thus, the motivation of this study is to figure out the weights of the criteria for quality improvement strategies in energy investments. Also, the most important contribution of this study to the literature is related to the originality in the methodology by proposing a new MCDM model while using hesitant linguistic term sets, linguistic 2-tuple information, interval-valued Pythagorean fuzzy sets properly. The findings indicate that empathy is the most significant criterion for the customer expectations in the energy investments. In addition to this issue, it is also identified that customization is the best factor among the technical requirements of energy investments. Moreover, information and communication facilities and organizational background are found as the best competencies of new service development in energy investments. Furthermore, that prior action and periodic action are the most prominent strategies for quality improvement. While considering these results, it can be said that the pricing policy of the energy companies should be fair to increase customer satisfaction. Additionally, offering flexible payment opportunities on energy bills can have a positive influence on the customer satisfaction in this process. Also, preliminary planning of the project should be done in detail in energy investments. Owing to this issue, customers' preferences can be identified before the product is placed on the market. In addition, it can be possible to identify the risks that may arise in energy investments with the help of the periodical audits.

Introducing a conceptual model for evaluating health safety environmental performance of residential buildings using the fuzzy decision-making approach.

Today, the issue of the physical and psychological safety of residents of residential buildings and their impact on the environment are major concerns for residents, builders, and sellers of the construction industry. The design and construction with the Health Safety, Environmental (HSE) approach can influence the direct and indirect costs of the construction industry and is considered an important criterion for pricing at a time of sell. Creating models that can demonstrate the degree of adherence of a building to safety, health, and environmental standards can be effective in the usage as well as the physical and mental comfort of residents using that building. Accordingly, the purpose of this research is to provide a conceptual model for determining the performance criteria of buildings with the HSE approach. This study was carried out based on the practical purpose of the research as well as on a descriptive-analytic method. In this study, the factors affecting HSE performance were first determined. Then, Decision-Making Trial and Evaluation Laboratory (DEMATEL) method was used in a fuzzy environment to measure cause and effect relationships. The findings of the research suggested that among the factors affecting building performance, the safety of the structure is the most influential factor, and the architectural welfare is the most important factor, which itself is in the category of influential factors and is affected by other factors. Creating structures that can assess the performance of a building with the Health Safety, Environmental (HSE) approach can be an important criterion in making decision at the time of designing, constructing, operating, purchasing, and housing for customers and residents of a building. This issue can be considered an indicator in the construction process. Government agencies, the insurer, and price-setting agent of buildings can also use this model for valuation and rank buildings and defining their premium rates.

A New Bi-Level Planning Approach to Find Economic and Reliable Layout for Large-Scale Wind Farm

This paper presents a bi-level planning approach to find an optimal layout for a large-scale wind farm (WF) from economic and reliability perspectives. The upper level of the planning approach is formulated as constrained multi-objective optimization (MOO) to obtain the optimal WF layout, where two conflicting objectives are optimized simultaneously. Two objectives for MOO are i) yearly gross energy production and ii) annual loan repayment (for cable and land area of the WF), where the first objective is maximized and the second objective is minimized. Jensen's wake model is used to calculate the wake effect, and to evaluate the multiple wake effect within a WF, a coordinate-transformation-based approach has been adopted in this study. An efficient hybrid multi-objective metaheuristic algorithm, which is based on nondominated sorting multi-objective particle swarm optimization and improved archive multi-objective simulated annealing, has been proposed to find the optimized WF layout. The superiority of the Pareto front obtained by the proposed algorithm for the large-scale WF layout is supported by its comparison with different powerful and well-established MOO algorithms. In the lower level of the proposed approach, economic and reliability analyses of the solutions (WF layout), obtained in the Pareto front by the proposed hybrid algorithm, have been done. In this context, two performance metrics, a) generation economy index and b) expected wind energy generation (EWEG), have been considered. A sequential Monte Carlo simulation has been developed to calculate the EWEG considering random failure of both wind turbines and cables in this paper. The most suitable WF layout is selected by trading off between economy and reliability using a fuzzy decision-making approach.

Multi-criteria decision making in Pythagorean fuzzy environment

Pythagorean fuzzy set, initially extended by Yager from intuitionistic fuzzy set, is capable of modeling information with more uncertainties in the process of multi-criteria decision making (MCDM), thus can be used on wider range of conditions. The fuzzy decision analysis of this paper is mainly built upon two expressions in Pythagorean fuzzy environment, named Pythagorean fuzzy number (PFN) and interval-valued Pythagorean fuzzy number (IVPFN), respectively. We initiate a novel axiomatic definition of Pythagorean fuzzy distance measurement, including PFNs and IVPFNs. After that, corresponding theorems are put forward and then proved. Based on the defined distance measurements, the closeness indexes are developed for both expressions, inspired by the idea of technique for order preference by similarity to ideal solution (TOPSIS) approach. After these basic definitions have been established, the hierarchical decision approach is presented to handle MCDM problems under Pythagorean fuzzy environment. To address hierarchical decision issues, the closeness index-based score function is defined to calculate the score of each permutation for the optimal alternative. To determine criterion weights, a new method based on the proposed similarity measure and aggregation operator of PFNs and IVPFNs is presented according to Pythagorean fuzzy information from decision matrix, rather than being provided in advance by decision makers, which can effectively reduce human subjectivity. An experimental case is then conducted to demonstrate the applicability and flexibility of the proposed decision approach. Finally, extension forms of Pythagorean fuzzy decision approach for heterogeneous information are briefly introduced to show its potentials on further applications in other processing fields with information uncertainties.

The Extend Customer Requirement Factors Based Service Level Evaluation for Manufacturing Enterprises

This study proposes a novel way to evaluate the enterprise customer service level (ECSL) for OEMs (Original Equipment Manufacturers). First, a set of service level evaluating metrics is established based on the extended customer requirement factors (ECRFs), which covers the whole service product delivery process to fully reflect enterprise customers' service requirement. Then, the hybrid fuzzy multiple-criteria decision-making approach combining the analytic hierarchy process (AHP) and the technique for order of preference by similarity to ideal solution (TOPSIS) are adopted. In the evaluating model, a fuzzy method is used to reflect the ambiguity in human thinking and decision making. The weight of each decision maker is determined by a two-layer way to make it more objective. The individual preferences are aggregated by AIP (aggregating individual priorities) way in the group decision-making process of the AHP to respect each decision makers' separate opinion. With the presented approach, ECSL can be evaluated and adjusted conveniently.

Selection of energy matrix sources in Chile using a fuzzy logic decision approach

Chile’s 2050 energy policy ultimate goals are to produce a sustainable model of economic growth respectful of the environment where energy is produced efficiently and reliably. Renewable energy sources are considered the main drive for developing by 2050 at least 70% of the total energy in Chile. This study aims to provide a quantitative analysis for the selection of the most sustainable energy production methods using the compromise ranking method (VIKOR) that uses maximum group utility for the majority and a minimum of individual regret for the opponent. Since all evaluations are provided via intervals, the possible degree theory is used to compare them. Nine major criteria are critically used for this purpose and prioritized using analytical hierarchical process (AHP). Since Chile’s energy production matrix still relies heavily on fossil fuels with major concerns of GHG emissions, all major potential energy sources in Chile are considered including ocean energy in addition to nuclear energy. This study shows that biomasses are the best compromise solution and that traditional and modern nuclear energy plants score consistently better than solar power. Large hydro power plants rank very high but in light of the social opposition present in the country, they might not be easy to build as hoped. Ocean power is far superior to geothermal energy and comparable to wind power and for this reason it should be considered together with nuclear power for the future Chilean energy matrix.

A novel hybrid approach based on fuzzy multi-criteria decision-making tools for assessing sustainable alternatives of power generation in San Andrés Island

This paper presents a novel approach based on fuzzy multi-criteria decision-making tools for assessing sustainable alternatives of power generation in San Andrés Island, Colombia. In the first stage, the energy system was established. A fuzzy multi-objective decision approach based on a mixed-integer linear model was implemented to obtain a set of alternatives, including solar photovoltaic, wind turbines, and the diesel plants currently used. Subsequently, the total cost and the CO2 emissions of the energy system were minimized all while considering design, operational, and efficiency constraints. The CO2 emissions and the total present value of the alternatives of energy, together with social, technological, economic, and environmental factors assessed through expert opinions were used as input in the fuzzy multi-criteria decision phase, where a novel fuzzy logic model was employed for selecting the most sustainable alternative. The results indicate that the current diesel capacity in San Andrés Island prevails; with a maximum participation of 3% and 4% of solar and wind systems, respectively.

Balanced scorecard-based analysis of investment decisions for the renewable energy alternatives: A comparative analysis based on the hybrid fuzzy decision-making approach

The aim of this study is to evaluate investment decisions for the renewable energy (RE) alternatives. For this purpose, balanced scorecard (BSC)-based 4 dimensions and 8 criteria are identified. Additionally, 5 different RE investment alternatives (biomass, hydropower, geothermal, wind and solar) are examined. DEMATEL method is used to weight these dimensions and criteria whereas RE investment alternatives are weighted by TOPSIS approach. The novelty of this study is that comparative analysis is applied by considering standard fuzzy, interval type-2 (IT2) fuzzy and IT2 hesitant fuzzy (HF) sets. The findings show that competition is the most significant dimension and persistence of research and development is the most important criterion. Furthermore, it is also determined that solar and wind energies have the best performance, but geothermal energy is on the last rank. Therefore, it is recommended that level of the competition in the RE markets should be mainly taken into the consideration by the investors. In other words, investors may have loss in this RE market when there is high competition. Another important point is that investors should also give importance to the development capacity of the RE market. The main reason is that in case of the possibility to improve the products in RE markets by making research and development, investment can lower their cost. Hence, the profitability of the RE investment can increase by examining the market in detail for this purpose.

A symbol-based fuzzy decision-making approach to evaluate the user satisfaction on services in academic digital libraries

Academic libraries play a significant role in providing core services that include research, teaching and learning. Usersatisfaction is an important indicator for evaluating the performance of library service. This paper develops a methodfor measuring the user satisfaction in a group decision-making environment. First, the performance of service isevaluated by using questionnaire survey. The scores are recorded by using some simple symbols. Second, the symbolinformation along with nonresponse items in questionnaires are fused into an intuitionistic fuzzy information. Third, anexperimental analysis is provided to illustrate the validity and effectiveness of introduced method in this paper. Finally,the theoretical and practical implications of current model are discussed, the important limitations are recognized, andsome main advantages and future research directions of current method are shown in conclusions.

Reduction of overhead in routing protocols for MANET using fuzzy set-based decision making

It is well-known that dynamic topology, mobility of nodes, infrastructure less property and absence of central coordinator; make the behaviour of mobile ad hoc network (MANET) uncertain. Routing is the major step in the operation of MANET and the establishment of route from source to destination thus becomes crucial. Routing decision is distributed among the nodes in the network and the reliable and effective routing predominantly depends on proper establishment of route from source to destination. Route establishment depends largely on control packets and those packets induce more overhead in the network, which in turn degrades the performance of the network. The present work proposes a novel method to reduce the control overhead by predicting the quality of the neighbouring nodes that sustain more, using a fuzzy set decision approach. The flooding of control packets is based on a fuzzy decision taken on success rate of each link in the previous trials and residual energy of the neighbouring nodes. Simulation study reveals that this approach significantly reduces the control overhead in the network and improves the overall performance.

IT2-Based Fuzzy Hybrid Decision Making Approach to Soft Computing

This aims to evaluate the risk appetite of the financial investors in emerging economies using an integrated interval type-2 fuzzy model. For this purpose, eight different criteria are identified with the supporting literature. The interval type-2 fuzzy DEMATEL approach is used to weight these criteria regarding the importance level. In addition, investors are classified into three different groups with respect to the risk appetite which are the aggressive/risk taker, moderate/risk neutral, and conservative/risk averse. Moreover, the interval type-2 fuzzy QUALIFLEX methodology is taken into consideration to rank these investor groups. The novelty of this paper is to propose a hybrid fuzzy decision-making approach to the investors’ risk appetite based on the interval type-2 fuzzy sets. The findings show that aggressive investors play the most important role in emerging economies. Therefore, financial products, which offer high returns, should be developed to attract the attention of these aggressive investors. Owing to this aspect, it can be possible for emerging economies to improve their financial systems.

Modelling the logistic processes using fuzzy decision approach

Logistic processes deal with the information about producing and distributing goods and services from one place to another to fulfill the customer requirements. Every kind of business requires the proper functioning of logistic processes for the success of company or organization. In retail businesses, facility location for logistic processes serves as a backbone and the success or a failure of the company depends upon the geographical location of the company. It is a multiple criteria decision making problem involves multiple criteria to analyze the proper location of a company. In this research work, at first, we developed a multi criteria based structural model in retail facility location selection based on logistic processes. Then by using fuzzy modelling technique, the criteria are converted into triangular fuzzy numbers. We have adopted the technique of order preference similarity to ideal solutions for finding the best alternative. We have also applied the sensitivity analysis on the suggested modelling technique and found the same alternative as best with high degree of certainty which confirms the reliability of the proposed modelling technique.

Balanced scorecard-based analysis about European energy investment policies: A hybrid hesitant fuzzy decision-making approach with Quality Function Deployment

This study aims at analyzing the performance results of the European policies in energy investment within an integrated multidimensional quality measurement approach. For this purpose, the quality function deployment is adopted to the multidimensional performance measurement based on the balanced scorecard method. The dimensions and criteria of customer and technical requirements, process design, and performance measurement are defined to measure each process of QFD (Quality Function Deployment) for the energy investment policies with the supported literature. Within this context, the customer and technical requirements for energy investment policies are evaluated by considering the fuzzy decision matrix in the first process of the QFD and then, the technical requirements are used to rank the new service/product process of the energy investments in the second process of QFD. The balanced scorecard perspectives and the key factors are defined to rank the European energy investment policies respectively. Accordingly, the possible priorities of the European energy investment policies are discussed to conduct the most remarkable and efficient energy operations and the relevant results to contribute the improvement of energy sector are highlighted.

RETRACTED: Interval optimization based performance of photovoltaic/wind/FC/electrolyzer/electric vehicles in energy price determination for customers by electricity retailer

Abstract This paper proposes optimal management of hydrogen storage systems and plug-in electric vehicles in the scheduling of retailer under pool market price uncertainty which real-time pricing is determined in comparison with time-of-use pricing and fixed pricing. Also, pool market price uncertainty is modeled via proposed interval optimization approach for uncertainty-based profit function of retailer. In the proposed model, uncertainty-based profit function of retailer is reformulated as a deterministic bi-objective framework with average and deviation profits as the conflict objective functions which deviation profit should be minimized while average profit should be maximized. Furthermore, weighted sum approach is used to solve the proposed bi-objective model in order to obtain Pareto solutions. Finally, fuzzy decision-making approach is provided to select the trade-off solution from Pareto solutions. The proposed MIP-based model is implemented in GAMS software which can be solved using CPLEX solver. Deterministic and interval optimization approaches under fixed, time-of-use, and real-time pricing are utilized in the case studies and the results are compared with each other in order to show the effectiveness of the proposed model. The obtained results show that deviation profit of retailer decreases in the proposed interval optimization approach in comparison with deterministic approach. Also, average profit of retailer increases in the real-time pricing in comparison with time-of-use pricing and fixed pricing.

Integrated fuzzy decision approach for reliability improvement of dam instrumentation and monitoring

Dams constitute a potential hazard to downstream life and property. Therefore, it is necessary to detect any signs of abnormal behaviour in structural safety. Monitoring of an embankment dam plays a key role to increase dam safety and to prove performances. Appropriate instrument selection is one of the most important steps of a monitoring plan. Inappropriate instruments may cause irreparable damages in critical situations. The lack of a method to analyse the instruments, and to select an appropriate one is one of the shortages of a monitoring plan. Nowadays, decision-making methods have been widely used to optimise the selection process. In addition, due to uncertainty in decisions, fuzzy methods are applied. The present study aims to establish an integrated decision model based on FAHP-FTOPSIS methods, by taking into account 9 influential criteria and 42 alternatives as geotechnical instruments. The model has been applied for a clay core embankment dam. Results showed that group decision-making can reliably be used to prioritise the instruments. For instance, the best instrument for monitoring stresses was hydraulic pressure cell while its closeness coefficient was .55. The possible choices were reliably selected and prioritised due to their adjacency to the ideal solution.

Assessment of safety culture among job positions in high-rise construction: a hybrid fuzzy multi criteria decision-making (FMCDM) approach

ABSTRACTThe construction industry is known as one of the most dangerous industries, which not only requires sound operation of executive laws and regulations, but also necessitates the safety culture of all workers at workshops. Therefore, the aim of this research is to identify the factors of safety culture and ranking occupations in jobsites based on those factors in order to proactively improve the safety culture of construction projects and subsequently promote safety conditions and worksites. In this study, safety culture criteria are weighted by a combination of Fuzzy Decision Trail and Evaluation Laboratory and Fuzzy ANP methods. Next, different job positions in high-rise projects are ranked using the Fuzzy Technique for Order of Preference by Similarity to Ideal Solution method. Findings demonstrated that the project manager, site superintendent and supervisor occupations had the highest and labourers had the lowest level of safety culture in the high-rise construction industry. Furthermore, factors such as safety supervision and training must be considered more seriously in order to create a positive safety culture among workers.

A Fuzzy Trade-Off Ranking Method for Multi-Criteria Decision-Making

The aim of this paper is to present a trade-off ranking method in a fuzzy multi-criteria decision-making environment. The triangular fuzzy numbers are used to represent the imprecise numerical quantities in the criteria values of each alternative and the weight of each criterion. A fuzzy trade-off ranking method is developed to rank alternatives in the fuzzy multi-criteria decision-making problem with conflicting criteria. The trade-off ranking method tackles this type of multi-criteria problems by giving the least compromise solution as the best option. The proposed method for the fuzzy decision-making problems is compared against two other fuzzy decision-making approaches, fuzzy Technique for Order Preference by Similarity to the Ideal Solution (TOPSIS) and fuzzy VlseKriterijuska Optimizacija I Komoromisno Resenje (VIKOR), used for ranking alternatives.

Multi-Objective Optimization Approach for Placement of Multiple DGs for Voltage Sensitive Loads

This paper presents the optimal placement of multiple Dispersed Generators using multi-objective optimization. The optimization is carried out with objectives namely active power loss, reactive power loss, voltage deviation and overall economy. The multi-objective optimization and accounting conflicting objectives are realized through Particle Swarm Optimization with fuzzy decision approach to find the optimal sizes and sites of Dispersed Generators for voltage dependent residential, commercial and industrial loads. The clusters of buses are formulated from base case load flow to limit the search space for finding the placement of the Dispersed Generators. The effectiveness of the proposed approach is tested on a 69-bus radial distribution. It is found that the optimal placement of the Dispersed Generators improves the overall performance of the system and the optimal allocation is affected by the type of load.