Subjective Judgments Of Decision Makers Research Articles

Weighted probability kernel multi-granularity three-way decision integrating GRA and its application in medical diagnosis

Three-way decision, an outstanding method to handle decision-making uncertainties, relies on essentially the loss functions derived from the Bayesian risk decision process. Actually, there are plentiful loss functions that depend on the subjective judgment of decision-makers under different decision scenarios, lacking uniform and objective measurement frameworks. This study pays attention to the real clinical diagnosis, and constructs a weighted probability kernel multi-granularity three-way decision method (WKMG-TWD) integrating gray relation analysis (GRA) over a multi-source heterogeneous decision information system (MHDIS). The method establishes a standardized data-driven calculation framework of loss functions. Foremost, the multi-kernel probabilistic similarity is defined and granularity's weights with knowledge consistency are explored. Subsequently, a weighted probability kernel multi-granularity rough set (WKMGRS) is constructed in this paper. Secondly, to introduce the three-way decision, this study proposes the cost-sensitive individual loss functions considering the correlation determined by GRA between decision objects and different decision classes. Ultimately, this study establishes and applies a three-way iterative classification model to hypertension diagnosis. The experimental results confirm the effectiveness and superiority of the model. The main contribution of this paper is twofold. One is to offer a uniform calculation framework for loss functions and granularity's weights. The other is to furnish invaluable guidance for solving complex medical decision-making problems.

An integrated fuzzy AHP and fuzzy TOPSIS approach for screening backfill materials for contaminant containment in slurry trench cutoff walls

The inclusion of backfill material is crucial for the effective containment of contaminants in a slurry trench cutoff wall. However, selecting the optimal backfill material is complex and involves multiple criteria. This study aimed to develop a new approach to assist in the selection process by rationally dealing with the subjective judgment of decision makers. The approach employed fuzzy analytic hierarchy process (AHP) and fuzzy technique for order preference by similarity to ideal solution (TOPSIS) methods. Initially, consistent judgment matrices were established based on a unique consulting questionnaire. The fuzzy AHP method used Buckley's method to calculate the fuzzy weights of pairwise comparisons. The fuzzy TOPSIS method was then employed to rank and evaluate four different backfill materials. The proposed methodology was successfully implemented at a real contaminated site in China to select the appropriate backfill material for construction of a slurry trench cutoff wall. Based on the proposed integrated methodology, fiber reinforced reactive magnesia-activated slag-soil-bentonite (FMSB) was determined as the most appropriate backfill materials for contaminant containment in slurry trench cutoff walls at the site reported in this study.

FMEA Based Fuzzy Topsis for Assessment of Quality Problems in Telescopic Platform Production

In order to increase process and product quality fast and least costly, it is very useful to focus on the process that causes the important quality problems. In this study, quality problems and related processes in a company that produces on-vehicle equipment in the automotive industry are examined. The purpose of this study is to provide a quality improvement perspective to reduce process and product defects. Fault Mode and Effects Analysis (FMEA) is applied to detect faults, determine their causes and prioritize them. Prioritization of critical quality errors is revealed using traditional FMEA and FMEA-based fuzzy Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). The FMEA-based fuzzy TOPSIS method has been proposed because of its ability to handle uncertainty arising from the subjective judgments of decision makers. The results are compared and the preventions are suggested to avoid from the most important process that causes the quality problem.

Evaluation of software development projects based on integrated Pythagorean fuzzy methodology

Implementing ERP (Enterprise Resource Planning) system successfully comes with a set of costly and complex challenges. The purpose of this paper is to offer an effective cloud-based ERP software evaluation framework to gain a better understanding of these complexities and address such challenges by identifying the selection criteria. The PFS (Pythagorean Fuzzy Set) is the new extension of Intuitionistic fuzzy sets, the Simple Additive Weighting (SAW) is an easy-to-use technique to determine the weights of the criteria, and the VIKOR technique is a compromise ranking methodology. In the recommended novel integrated MCDM (Multi-Criteria Decision-Making) methodology, Decision-Makers (DMs) must choose the best one among a set of candidate alternatives that satisfies the evaluation criteria. The GDM (Group Decision Making) is preferred here to deal with hesitancy in the evaluation of alternatives under group preferences. The sensitivity analysis resulted from various scenarios reveals that the proposed method is quite sensitive to criteria weights. The service and support, cost, and functionality are found as the essential evaluation criteria for the Turkish firm. These findings emphasize the significance of a qualified group of DMs for the evaluation process. The case study findings demonstrate that the developed approach is practical and validated for solving software development projects. This study presents a novel integrated methodology based on the PFS, SAW, and VIKOR to measure the performance of software development projects, to deal with the ambiguity and imprecision caused by the subjective judgments of DMs. The research contributes to the literature by delivering a combined decision methodology for the first time and by applying it to evaluate the software development projects.

The Core of Uncertain Coalitional Game Based on Hurwicz Criterion with Application to Cyber Security Information Sharing

The coalitional game focuses on how people share the payoffs of collaboration when they form coalitions. However, we cannot accurately obtain the different coalitions’ payoffs because of the actual situation’s limitation or economic and technical factors. Therefore, we have to rely on experts in the field to estimate the likelihood of various events and give their belief degrees. To deal with the belief degrees, scholars of uncertainty theory suppose the transferable payoffs to be uncertain variables and propose the uncertain coalitional game. Many expected and optimistic solution concepts have been put forward in the literature, even though the expected value criterion does not consider the decision-maker’s attitude to risk, and the optimistic value criterion is too extreme. To better describe the different subjective judgments of decision-makers, the Hurwicz criterion is applied to the uncertain coalitional game, in which the players intend to maximize their Hurwicz payoffs. Besides, the method to discover the Hurwicz-core is provided, and the condition that the core is nonempty is proved. What’s more, the Hurwicz–Shapley value is mathematically proven to be in the Hurwicz-core in a convex uncertain coalitional game. An application in cyber security information sharing is provided.

Evaluating the sustainability of big data centers using the analytic network process and fuzzy TOPSIS.

The big data revolution has created data center sustainability problems, whose solutions require the consideration of environmental factors. The purpose of this study is to establish a big data center sustainability evaluation index and provide guidance for sustainable data center construction. This research formulated a big data center sustainability evaluation model that integrates multiple-criteria decision-making methods based on the analytic network process and fuzzy technique for order preference by similarity to an ideal solution (TOPSIS). Furthermore, a case study was used to examine the proposed model. The refrigeration system, layout and ventilation, data center location, data volume, and server power consumption are the five most crucial factors in determining the sustainability level of a big data center. The areas that require further development are the balancing of tasks on different IT equipment, renewable energy use, and waste heat utilization. This research provides a method or guide that can be used by managers when they build new big data centers or upgrade and optimize existing big data centers to make them more sustainable. This study is the first to assess the sustainability of a big data center according to multiple criteria decision-making methods, in which fuzzy theory is applied to evaluate the imprecise and subjective judgments of decision-makers. This study provides a systematic evaluation framework that is based on qualitative and quantitative criteria and comprises the four factors of big data level, equipment level, room level, and data center level. Big data is new oil, but it is not clean oil. It is both a vital driver of economic growth and a source of environmental damage. We need to ensure that big data centers are run in a sustainable way.

Study on Hesitant Fuzzy Multiattribute Quality Evaluation Based on Surface Defect Information of Autobody Panels

Surface defects of autobody panels have the greatest impact on the surface quality of the automobile body, but many enterprises lack a scientific and reasonable evaluation method of surface quality, relying solely on the subjective judgment of decision makers which will lead to an increase in the probability of misjudgment. In this paper, the subjective weight is determined by the genetic algorithm based on optimization, and the objective weight is determined by the improved deviation maximization method. Combining the hesitant fuzzy set theory, the hesitant fuzzy mixed weighted arithmetic average operator (HFHWA), and the score function, the surface defect information of the panel is quantified. On this basis, a complete set of hesitant fuzzy multiattribute evaluation model of surface defect information is proposed. Taking a batch of inner panels of the automobile door produced by A automobile enterprise as an example, five common defects including hidden pit, bump and scratch, rust, indentation pockmark, and ripple are selected as evaluation attributes to evaluate their surface quality, which verifies the validity and practicability of the model.

SOLAR PV POWER PLANT LOCATION SELECTION USING A Z- FUZZY NUMBER BASED AHP

One of the most used renewable energy systems to produce clean and sustainable energy are solar energy photovoltaic (PV) plants. The selection among solar energy PV plant location alternatives requires a multi-criteria decision making approach with several conflicting and linguistic criteria. The assessment process is generally done in a vague and imprecise environment. Fuzzy set theory is often very beneficial for evaluating the subjective judgments of decision makers. The Analytic Hierarchy Process is the most used multi-criteria decision making method in the world because of its simplicity and efficiency. In this paper, we select a location for a solar energy PV plant using a 4-level hierarchy. We consider several criteria and sub-criteria including initial cost, maintenance cost, slope and distance to highways. A Z-fuzzy number is a relatively new concept in fuzzy set theory that enables one to circumvent the limitations of ordinary fuzzy numbers. Z-fuzzy numbers can be viewed as a combination of crisp numbers, intervals, fuzzy numbers and random numbers because of their generality. They give a better representation than ordinary fuzzy numbers. This study solves the multi-criteria solar PV power plant location selection problem with a Z-fuzzy based AHP method. To check the applicability of the method proposed here, a real-life case study from Turkey is presented and solved.

An extended TODIM-PROMETHEE method for waste-to-energy plant site selection based on sustainability perspective

The waste-to-energy (WtE) project has attracted much attention from the society mainly because of the characteristic of environmental friendliness. And plant site selection occupies a prominent position during the whole life cycle of waste-to-energy project. In consideration of the ambiguity of subjective judgments of decision makers (DMs) and the compensation problem existing in decision process, we build a framework for WtE plant site selection decision utilizing a novel method with triangular intuitionistic fuzzy numbers (TIFNs). First of all, the criteria for optimal WtE plant siting are determined based on extended sustainability theory including four perspectives of economic, environment, society, and technology to meet the demand of current social development. Then, the TIFNs and the triangular intuitionistic fuzzy weighted geometric (TIFWG) operator are applied to describing the indefinite information and completing the conversion, so that the uncertainty and hesitation of decision information can be well expressed. Furthermore, the extended TODIM (an acronym in Portuguese of interactive and multiple attribute decision making) method in conjunction with PROMETHEE-II (Preference Ranking Organization Method for Enrichment Evaluations) method is utilized to rank the alternatives, which makes this framework more practical and applicable. Finally, a case from China certifies the validity of the proposed framework.

Optimal Contractor Selection in Construction Industry: The Fuzzy Way

A purely price-based approach to contractor selection has been identified as the root cause for many serious project delivery problems. Therefore, the capability of the contractor to execute the project should be evaluated using a multiple set of selection criteria including reputation, past performance, performance potential, financial soundness and other project specific criteria. An industry-wide questionnaire survey was conducted with the objective of identifying the important criteria for adoption in the selection process. In this work, a fuzzy set based model was developed for contractor prequalification/evaluation, by using effective criteria obtained from the percept of construction professionals, taking subjective judgments of decision makers also into consideration. A case study consisting of four alternatives (contractors in the present case) solicited from a public works department of Pondicherry in India, is used to illustrate the effectiveness of the proposed approach. The final selection of contractor is made based on the integrated score or Overall Evaluation Score of the decision alternative in prequalification as well as bid evaluation stages.

Computing the weights of criteria with interval-valued fuzzy sets for MCDM problems

In the real world, many influenced factors or criteria should be considered in the multiple criteria decision-making (MCDM) process. Face to the uncertain environment, the decision makers or experts always cannot express their opinions exactly in the decision-making process. Under this situation, interval-valued fuzzy sets are suitable used to represent the subjective judgments of decision makers. In this paper, the fuzzy AHP method is applied to compute the fuzzy weights of each criterion based on the interval-valued fuzzy sets. The proposed method can provide a more flexible way for decision makers to express their subjective opinions. A systematic method is presented here to compute the fuzzy weights of criteria for dealing with a MCDM problem. An example is presented to illustrate the computational procedure of the proposed method. Conclusions and future research direction will be discussed at the end of this paper.

Hybridising Human Judgment, AHP, Grey Theory, and Fuzzy Expert Systems for Candidate Well Selection in Fractured Reservoirs

The selection of appropriate wells for hydraulic fracturing is one of the most important decisions faced by oilfield engineers. It has significant implications for the future development of an oilfield in terms of its productivity and economics. In this study, we developed a fuzzy model for well selection that combines the major objective criteria with the subjective judgments of decision makers. This was done by fusing the analytic hierarchy process (AHP) method, grey theory and an advanced version of fuzzy logic theory (FLT). The AHP component was used to identify the relevant criteria involved in selecting wells for hydraulic fracturing. Grey theory was used to determine the relative importance of those criteria. Then a fuzzy expert system was applied to fuzzily process the aggregated inputs using a Type-2 fuzzy logic system. This undertakes approximate reasoning and generates recommendations for candidate wells. These techniques and technologies were hybridized by using an intercommunication job-sharing method that integrates human judgment. The proposed method was tested on data from an oilfield in Western China and finally the most appropriate candidate wells for hydraulic fracturing were ranked in order of their projected output after fracturing.

Uticaj subjektivnih procjena donosioca odluka na investicionu odluku

Uticaj subjektivnih procjena donosioca odluka na investicionu odluku

Penentuan Priorita Perbaikan Jalan Berbasis Metode Analytic Network Process Sebagai Komponen Menuju Kota Cerdas

Smart city become a demand for people to live in more comfort and easier. Knowledge is needed in every decision support system in smart city. This paper presents a research in determining the priority order of road handling based on level of service by using Analytic Network Process which is implemented into decision support systems as a component toward smart city. Variables used refers to the Highway Capacity Manual Indonesia based on the volume of traffic and the road characteristic data. Analytic Network Process is used because of its advantages in conducting multi-criteria assessment on the basis of the subjective judgment of decision makers and can combine quantitative and qualitative data. From the results of the validation test between the system output and outcome data field issued by Dishubinkom Cirebon, the accuracy of the test results of 10 streets in the city of Cirebon with validation test Spearman Rank correlation is equal to 0.867. The results showed Analytic Network Process can be implemented and an appropriate solution indetermining the road handling priority.

Urban Transportation Vehicle Sustainability Assessment with a Comparative Study of Weighted Sum and Fuzzy Methods

AbstractSustainability assessment in transportation planning and selection of the best transportation mode among alternatives is a challenging process. The technological differences among conventional, hybrid, and alternative fuel vehicles and buses, the large number of variables in the sustainability assessment of transportation systems, and the subjective judgment of decision makers introduce uncertainty. The objective of this paper is thus twofold: (1) to demonstrate a sustainability framework that focuses specifically on vehicle characteristics and (2) to compare two multicriteria decision making (MCDM) methods in terms of ranking sustainability performance of transportation vehicles and applicability to selected indicators. The two most widely adopted MCDM methods for decision making were used, the weighted sum method for its simplicity and the fuzzy logic method for its ability to incorporate imprecise and vague information. The assessment includes five vehicle types and various mode share scenarios...

Fuzzy copula model for wind speed correlation and its application in wind curtailment evaluation

Wind parks always produce diverse percentages of their nominal power at the same time, leading to a concern about correlation between wind speeds. The assessments of wind speed correlation have been particularly focused on probabilistic modeling of aleatory uncertainty. However, poor historical data, imprecise parameter estimation and incomplete knowledge of wind speeds lead to another type of uncertainty, possibilistic uncertainty, which requires an explicit analysis. Therefore, a fuzzy copula model is firstly proposed to express the possibilistic uncertainty of wind speed correlation. The advantage of the proposed model is that the copula parameters can be interval numbers, triangular or trapezoidal fuzzy numbers based on the wind speed data and subjective judgment of decision makers. For estimating copula parameters, a complete decision rule and interval estimation method is developed based on cumulative probability and probability distributions of correlated wind speeds. The effectiveness of the proposed model is validated by the application in wind curtailment evaluation while a method is developed to evaluate and quantify wind curtailment in a hybrid power system involving different types of generation. The results demonstrate that the proposed model and method are capable of describing the possibilistic uncertainty and evaluating its effect on wind curtailment. Compared with previous research, the proposed model develops a new universal parameter estimation method and selection rule to provide more interval results, by calculating the membership function of copula parameters and wind curtailment. System planners and operators can apply the fuzzy results to various topics like reserve capacity evaluation or real-time dispatch depending on their level of risk tolerance.

Planning renewable energy in electric power system for sustainable development under uncertainty – A case study of Beijing

An interval type-2 fuzzy fractional programming (IT2FFP) method is developed for planning the renewable energy in electric power system for supporting sustainable development under uncertainty. IT2FFP can tackle output/input ratio problems where complex uncertainties are expressed as type-2 fuzzy intervals (T2FI) with uncertain membership functions. The IT2FFP method is then applied to planning Beijing electric power system, where issues of renewable energy utilization, electricity supply security, and pollutant/greenhouse gas (GHG) emissions mitigation are incorporated within the modeling formulation. The obtained results suggest that the coal-fired power would continue to decrease and the share of renewable energy in gross electricity supply would maintain an increasing trend. Results also reveal that imported electricity plays a significant role in the city’s energy supply. A number of decision alternatives are also analyzed based on the interval solutions as well as the projected applicable conditions, which represent multiple options with sustainable and economic considerations. The optimal alternative that can give rise to the desirable sustainable option under the maximization of the share of renewable power generation has been suggested. The findings can help decision makers identify desired alternatives for managing such a mixed energy system in association with sustainable development. Compared with the conventional optimization methods that optimize single criterion, it is proved that IT2FFP is advantageous in balancing conflicting objectives and reflecting complicated relationships among multiple system factors as well as in tackling various subjective judgments of decision makers with different interests and preferences.

Optimal site selection of electric vehicle charging station by using fuzzy TOPSIS based on sustainability perspective

Selecting the most sustainable site plays an important role in the life cycle of electric vehicle charging station (EVCS), which needs to consider some conflicting criteria. Different from the previous studies which mostly utilize programming (optimization) models, this paper employed a multi-criteria decision-making (MCDM) method to consider some subjective but important criteria for EVCS site selection. To reflect the ambiguity and vagueness due to the subjective judgments of decision makers, fuzzy TOPSIS method was applied to select the optimal EVCS site. Based on academic literatures, feasibility research reports and expert opinions in different fields, the evaluation index system for EVCS site selection was built from sustainability perspective, which consists of environmental, economic and social criteria associated with a total of 11 sub-criteria. Then, the criteria performances of different alternatives and criteria weights were judged by five groups of expert panels in the fields of environment, economy, society, electric power system and transportation system. Finally, the EVCS site alternatives were ranked by employing fuzzy TOPSIS method. The result shows EVCS site A2 located at Changping district in Beijing obtains the highest ranking score and should be selected as the optimal site. Meanwhile, the environmental and social criteria are paid more attentions from decision makers than economic criteria. The sensitivity analysis results indicate the alternative A2 always secures its top ranking no matter how sub-criteria weights change. It is effective and robust to apply fuzzy TOPSIS method into EVCS site selection. This paper provides a new research perspective for site selection and also extends the application domains of fuzzy TOPSIS method.

Evaluating performance of Iranian cement firms using an integrated fuzzy AHP–VIKOR method

In today’s competitive environment, a firm’s performance evaluation and its comparison with other companies is an important issue for investors, creditors and companies in order to reach their investment goals. They can also develop their place to increase their revenue. The aim of this study is presenting a model based on fuzzy analytic hierarchy process (FAHP) and VIKOR (Vlse Kriterijumska Optimizacija Kompromisno Resenje) method. This combined method (fuzzy AHP–VIKOR) in the firm’s performance evaluation is presented by financial ratios. In this research, the proposed method is utilized in evaluating the performance of 27 Iranian cement firms in the Tehran stock exchange market for 2years (2008 and 2009), separately. The FAHP method is used to determine weights of criteria taking the subjective judgments of decision makers. VIKOR method is then applied for ranking the firms.

A Novel Multiperson Game Approach for Linguistic Multicriteria Decision Making Problems

Game theory is considered as an efficient framework in dealing with decision making problems for two players in the competitive environment. In general, the evaluation values of payoffs matrix are expressed by crisp values in a game model. However, many uncertainties and vagueness should be considered due to the qualitative criteria and the subjective judgment of decision makers in the decision making process. The aim of this study is to develop an effective methodology for solving the payoffs matrix with linguistic variables by multiple decision makers in a game model. Based on the linguistic variables, the decision makers can easily express their opinions with respect to criteria for each alternative. By using the linear programming method, we can find the optimal solution of a game matrix in accordance with the combination of strategies of each player effectively. In addition, the expected performance value (EPV) index is defined in this paper to compare the competition ability of each player based on the optimal probability of each strategy combination. And then, numerical example will be implemented to illustrate the computation process of the proposed model. The conclusion and future research are discussed at the end of this paper.