Aggregation operators on intuitionistic trapezoidal fuzzy number and its application to multi-criteria decision making problems

Intuitionistic trapezoidal fuzzy numbers and their operational laws are defined. Based on these operational laws, some aggregation operators, including intuitionistic trapezoidal fuzzy weighted arithmetic averaging operator and weighted geometric averaging operator are proposed. Expected values, score function, and accuracy function of intuitionitsic trapezoidal fuzzy numbers are defined. Based on these, a kind of intuitionistic trapezoidal fuzzy multi-criteria decision making method is proposed. By using these aggregation operators, criteria values are aggregated and integrated intuitionistic trapezoidal fuzzy numbers of alternatives are attained. By comparing score function and accuracy function values of integrated fuzzy numbers, a ranking of the whole alternative set can be attained. An example is given to show the feasibility and availability of the method.

Multi-criteria linguistic interval group decision-making approach

For group decision-making problems with linguistic assessment information, a new method based on two-tuple and WC-OWA operator is proposed, in which the criteria＇s weights and the decision-makers＇ preference information might take the form of linguistic grade, or might be between two continuous linguistic grades, or might be linguistic interval, or might be default. In this method, all linguistic values are transformed into two-tuple, and an aggregative decision-making matrix is obtained by using interval operation. The group aggregative values of each criterion on alternatives are computed by using a WC-OWA operator, the aggregative values on alternatives are worked out, and transformed into two-tuple. And the rank of the alternatives is obtained by using the order property of two-tuple. An example shows the feasibility and effectiveness of the proposed method.

Multi-criteria group decision making with fuzzy data:an extension of the VIKOR method

The VIKOR method is a multi-criteria decision making aid, which employs linear normalization to offer compromise solu- tions and has been successfully applied to various group decision making problems. However, the conventional VIKOR techniques used to integrate group judgments and the information loss arising from defuzzification are problematic and distort final outcomes. An improved integration method, which is optimization-based, is proposed. And it can handle fuzzy criteria values and weights. The precondition for accurately defuzzifying triangular fuzzy num- bers is identified. Several effective defuzzification procedures are proposed to improve the extant VIKOR, and a comprehensive evaluation framework is offered to aid multi-criteria group decision making. Finally, a numerical example is provided to illustrate the practicability of the proposed method.

Prospect Theory Based Hesitant Fuzzy Multi-Criteria Decision Making for Low Sulphur Fuel of Maritime Transportation

The environmental impact of maritime transport has now become a relevant issue in sustainable policy formulation and has attracted increasing interest from academia.For the sustainable development of maritime transport,International Maritime Organization stipulates that the sulfur content of ship emissions will reach 0.5 from 2020.With the approaching of the stipulated implementation date,shipowners need to adopt scientific methods to make decision on low sulfur fuel.In this study,we applied a prospect theory based hesitant fuzzy multi-criteria decision-making model to obtain the optimal decision of low Sulphur marine fuel.For this purpose,the hesitant fuzzy decision matrix is established to collect expert opinions,the maximizing deviation method is adopted to determine criteria weights.According to calculate the Euclidean distance from the reference points,we obtain the comprehensive prospect values of alternatives.Lastly,a case study is carried out to illustrate the significance and effectiveness of the proposed methodology.The innovation of this study is that it is the first-time adopting prospect theory and hesitate fuzzy sets to multi-criteria decision making for low Sulphur marine fuel,which provides an effective decision model for shipping companies under Low Sulphur regulations,and can also be extended to other industries.

Factors Affecting Selection of Elective Courses:The Use of Multi-Criteria Decision Making Model

Elective course selection has always been a serious and important decision making process for students in institutions. The aim of this study is to determine weights of factors affecting elective course selection from students' perspective. So as to solve the problem, Analytic Hierarchy Process (AHP) based model was used. Factors which affect the elective course selection from students' point of view include five main criteria and 13 sub-criteria which were indicated by students. An online questionnaire containing demographic questions, enabled each student to compare the relative priority of criteria with all of the other criteria. The responses were evaluated via Super Decisions software, and priorities were determined using the Analytic Hierarchy Process (AHP). According to the analysis of 40 experts (i.e., graduate students studying in engineering programs), course schedule and teaching staff related factors are the two most important factors affecting the elective course selection. A real- life situation which will help students who are indecisive and hesitates while selecting an elective course was observed. AHP contributes to develop an analytic and comprehensive framework decision making. The method should be considered by faculty member involved in decisions about curriculum update and offering new courses.

A Multi-Criteria Decision Making for the Unrelated Parallel Machines Scheduling Problem

In this paper, we propose a multi-criteria machine-schedules decision making method that can be applied to a produc-tion environment involving several unrelated parallel machines and we will focus on three objectives: minimizing makespan, total flow time, and total number of tardy jobs. The decision making method consists of three phases. In the first phase, a mathematical model of a single machine scheduling problem, of which the objective is a weighted sum of the three objectives, is constructed. Such a model will be repeatedly solved by the CPLEX in the proposed Multi-Objective Simulated Annealing (MOSA) algorithm. In the second phase, the MOSA that integrates job clustering method, job group scheduling method, and job group – machine assignment method, is employed to obtain a set of non-dominated group schedules. During this phase, CPLEX software and the bipartite weighted matching algorithm are used repeatedly as parts of the MOSA algorithm. In the last phase, the technique of data envelopment analysis is applied to determine the most preferable schedule. A practical example is then presented in order to demonstrate the applicability of the proposed decision making method.

Selection of Renewable Energy Based on Life Cycle Assessment and Multi-Criteria Decision Making

The development of renewable energy has become an important issue nowadays owing to the growing concerns about global warming and shortage of fossil fuels. The present study proposes an approach that integrates life cycle assessment (LCA), 3E (Energy-Economics-Environment) indicators and multi-criteria analysis (MCA) to evaluate environmental impacts and find the best choice or better choices among various renewable energy development plans. Several alternatives of wind turbines and photovoltaic (PV) systems are considered in the case study since they are found to be more feasible in Taiwan in a preliminary study. By using the proposed approach, the result indicates that the major environmental impacts arising from the development of wind turbines and PV systems in Taiwan are the generation of respiratory inorganics and minerals as well as the consumption of fossil fuels. Based on experts’ opinions, the outcome of multi-criteria analysis suggests that wind turbines have more advantages than PV systems in Taiwan. In particular, among the studied systems, a 2500-kW offshore wind turbine system has the greatest integrated performance, and a 4500-kW onshore wind turbine system comes in second.

Multi-criteria decision making for nuclear power plant selection using fuzzy AHP:Evidence from Indonesia

In terms of planning aspect,nuclear power plant(NPP)development needs analyses,consideration,and right decision making due to multi criteria involved.This study prioritizes the best site development of Indonesian NPPs in terms of 21 social,economic,and technical perspectives which comprise transmission network,oper-ating cost,economic impact,geology,geotechnic,seismology,population density,environment,cooling water,meteorology,hydrology,proximity to hazardous facilities,topography,land use,proximity to wetland,evacu-ation route,security,transportation network,legal consideration,impact of tourism,land ownership,historical places,and public acceptance,all identified to be considerations for the best sites.Two Fuzzy algorithms(Chang’s Extent Analysis and Buckley’s Fuzzy AHP)were used to determine the criteria priorities as well as NPP site feasibility of two locations in Indonesia.The results found that geology,geotechnic,and seismology(SA1);security(SO1),population density(SA2),environment(SA3),and cooling water(SA4)had the highest priorities among the 21 criteria.Based on the 5 top priority criteria,West Kalimantan and East Kalimantan provinces serve as the best candidates for the NPP sites.Such an innovative and novel multi criteria Fuzzy AHP–based decision making(MCDM)approach has been proven to become a useful reference to select NPP sites in Indonesia.

Multi-Criteria Decision Making Based on Correlation Coefficient of Triangular Intuitionistic Fuzzy Numbers

We study a multi-criteria fuzzy decision-making method based on weighted triangular intuitionistic fuzzy number correlation coefficients. Under the scenario that criteria weights for alternatives are completely unknown, triangular intuitionistic fuzzy method can not only supplement the insufficiency of the method based on the distance but also endow more information to the estimation and reduce the loss of evaluation information.Among the triangular numbers, two boundary numbers are the maximum and minimum values of the interval respectively, and the medium number is the most possible value under subjective estimation. Using this method,we propose a new way to obtain the criteria weights with more information quantity. By ranking the relative closeness of the weighted correlation coefficients between each alternative, and the critical and ideal alternatives,we show the method to figure out the most suitable alternative based on the expected criteria. An illustrative example is also taken into account to prove the effectiveness of the model.

Multi-criteria decision making method based on improved cosine similarity measure with interval neutrosophic sets

Purpose–The fuzziness and complexity of evaluation information are common phenomenon in practical decision-making problem,interval neutrosophic sets(INSs)is a power tool to deal with ambiguous information.Similarity measure plays an important role in judging the degree between ideal and each alternative in decision-making process,the purpose of this paper is to establish a multi-criteria decision-making method based on similarity measure under INSs.Design/methodology/approach–Based on an extension of existing cosine similarity,this paper first introduces an improved cosine similarity measure between interval neutosophic numbers,which considers the degrees of the truth membership,the indeterminacy membership and the falsity membership of the evaluation values.And then a multi-criteria decision-making method is established based on the improved cosine similarity measure,in which the ordered weighted averaging(OWA)is adopted to aggregate the neutrosophic information related to each alternative.Finally,an example on supplier selection is given to illustrate the feasibility and practicality of the presented decision-making method.Findings–In the whole process of research and practice,it was realized that the application field of the proposed similarity measure theory still should be expanded,and the development of interval number theory is one of further research direction.Originality/value–The main contributions of this paper are as follows:this study presents an improved cosine similarity measure under INSs,in which the weights of the three independent components of an interval number are taken into account;OWA are adopted to aggregate the neutrosophic information related to each alternative;and a multi-criteria decision-making method using the proposed similarity is developed under INSs.

INTEGRATING COMPLEX SYSTEM DYNAMICS OF PANDEMIC INFLUENZA WITH A MULTI-CRITERIA DECISION MAKING MODEL FOR EVALUATING PUBLIC HEALTH STRATEGIES

Recent developments in computational sciences and computer modeling have allowed emergency preparedness exercises to include simulation models as supporting tools. These simulation models are generally built for predicting temporal and geographic patterns of disease spread. However sole use of simulation models in exercise design falls short in terms of incorporating policy decision makers＇ preferences into decision-making processes. In this paper, a general framework for exercising public health preparedness plans with a decision support system is presented to integrate estimation of key epidemiological parameters with a system dynamics model of an outbreak. A multi-criteria decision making framework, an Analytical Hierarchy Process model, is then developed and integrated with the simulation model to help public health policy makers prioritize their response goals and evaluate mitigation strategies in a table-top exercise environment.

Trapezoidal Intuitionistic Fuzzy Aggregation Operator Based on Choquet Integral and Its Application to Multi-Criteria Decision-Making Problems

The Choquet integral can serve as a useful tool to aggregate interacting criteria in an uncertain environment. In this paper, a trapezoidal intuitionistic fuzzy aggregation operator based on the Choquet integral is proposed for multi-criteria decision-making problems. The decision information takes the form of trapezoidal intuitionistic fuzzy numbers and both the importance and the interaction information among decision-making criteria are considered. On the basis of the introduction of trapezoidal intuitionistic fuzzy numbers, its operational laws and expected value are defined. A trapezoidal intuitionistic fuzzy aggregation operator based on the Choquet integral is then defined and some of its properties are investigated. A new multi-criteria decision-making method based on a trapezoidal intuitionistic fuzzy Choquet integral operator is proposed. Finally, an illustrative example is used to show the feasibility and availability of the proposed method.

A decision model for decentralized autonomous organization platform selection: Three industry case studies

Context:Decentralized autonomous organizations are a new form of smart contract-based governance.Decentralized autonomous organization platforms,which support the creation of such organizations,are becoming increasingly popular,such as Aragon and Colony.Selecting the best fitting platform is challenging for organizations,as a significant number of decision criteria,such as popularity,developer availability,governance issues and consistent documentation of such platforms,should be considered.Additionally,decision-makers at the organizations are not experts in every domain,so they must continuously acquire volatile knowledge regarding such platforms.Objective:Supporting decision-makers in selecting the right decentralized autonomous organization platforms by designing an effective decision model is the main objective of this study.We aim to provide more insight into their selection process and reduce time and effort significantly by designing a decision model.Method:This study presents a decision model for the decentralized autonomous organization platform selection problem.The decision model captures knowledge regarding such platforms and concepts systematically.This model is based on an existing theoretical framework that assists software engineers with a set of multi-criteria decision-making problems in software production.Results:We conducted three industry case studies in the context of three decentralized autonomous organizations to evaluate the effectiveness and efficiency of the decision model in assisting decision-makers.The case study participants declared that the decision model provides significantly more insight into their selection process and reduces time and effort.Conclusion:We observe in the empirical evidence from the case studies that decision-makers can make more rational,efficient,and effective decisions with the decision model.Furthermore,the reusable form of the captured knowledge regarding decentralized autonomous organization platforms can be employed by other researchers in their future investigations.

A Hybrid MCDM Approach Based on ANP and TOPSIS for Facility Layout Selection

Facility layout selection is a multi-criteria decision making (MCDM) problem,since it has a strategic impact on the efficiency of manufacturing system.In view of the interdependency among selection criteria,analytic network process (ANP) is proposed to analyze the structure of the facility layout selection problem and determine the weights for each criterion.A network structure is constructed that shows all elements and clusters and their interactions.Limit priorities are also calculated which help decision maker evaluate the relative importance among criterion in the alternative selection process.Moreover,a hybrid MCDM approach that employs ANP and technique for order preference by similarity to an ideal solution (TOPSIS)method to rank the optimal facility layout alternatives.Finally,an application of a new aeronautic component assembly workshop facility layout selection is conducted.To further illustrate the advantage of the proposed approach,the difference between ANP-TOPSIS and AHP-TOPSIS methods are compared and discussed.Results have demonstrated the effectiveness and feasibility of the proposed method.

Location-allocation modeling for emergency evacuation planning with GIS and remote sensing:A case study of Northeast Bangladesh

This work developed models to identify optimal spatial distribution of emergency evacuation centers(EECs)such as schools,colleges,hospitals,and fire stations to improve flood emergency planning in the Sylhet region of northeastern Bangladesh.The use of location-allocation models(LAMs)for evacuation in regard to flood victims is essential to minimize disaster risk.In the first step,flood susceptibility maps were developed using machine learning models(MLMs),including:Levenberg-Marquardt back propagation(LM-BP)neural network and decision trees(DT)and multi-criteria decision making(MCDM)method.Performance of the MLMs and MCDM techniques were assessed considering the area under the receiver operating characteristic(AUROC)curve.Mathematical approaches in a geographic information system(GIS)for four well-known LAM problems affecting emergency rescue time are proposed:maximal covering location problem(MCLP),the maximize attendance(MA),p-median problem(PMP),and the location set covering problem(LSCP).The results showed that existing EECs were not optimally distributed,and that some areas were not adequately served by EECs(i.e.,not all demand points could be reached within a 60-min travel time).We concluded that the proposed models can be used to improve planning of the distribution of EECs,and that application of the models could contribute to reducing human casualties,property losses,and improve emergency operation.

Balanced scorecard-based analysis of customer expectations for cosmetology services:a hybrid decision modeling approach

The goal of this study is to analyze and characterize customer expectations in the cosmetics sector.Within this framework,first,the extant literature is reviewed,and 12 most prominent performance measurement criteria are identified.Then,these criteria are organized along the four different balanced scorecard dimensions.By employing an Interval Type-2 Fuzzy DEMATEL methodology,the weighted importance of these dimensions and criteria are identified.Additionally,with the Interval Type-2 Fuzzy TOPSIS approach,13 leading cosmetic service providers in Ukraine are ranked based on their relative scores.The findings of the study indicate that consumer is the most significant dimension while learning and growth seem to have the least importance.Similarly,it is also concluded that all consumerfocused criteria(i.e.diversification of services,feedback on the product and services,and customer loyalty)have the highest priorities in the complete criterion set.

Monte Carlo Analytic Hierarchy Process (MAHP) approach to selection of optimum mining method

One of the most critical and complicated steps in mine design is a selection of suitable mining method based upon geological,geotechnical,geographical,safety and economical parameters.The aim of this study is developing a Monte Carlo simulation to selection the optimum mining method by using effective and major criteria and at the same time,taking subjective judgments of decision makers into consideration.Proposed approach is based on the combination of Monte Carlo simulation with conventional Analytic Hierarchy Process(AHP).Monte Carlo simulation is used to determine the confdence level of each alternative’s score,is calculated by AHP,with the respect to the variance of decision makers’opinion.The proposed method is applied for Jajarm Bauxite Mine in Iran and eventually the most appropriate mining methods for this mine are ranked.

A MCDM-based model for vendor selection:a case study in the particleboard industry

We investigated procurement of raw materials for particleboard to minimize costs and develop an efficient optimization model for product mix. In a multiple-vendor market, vendors must be evaluated based on specified criteria. Assuming sourcing from the highest-scoring vendors, annual purchase quantities are then planned. To meet procure- ment needs, we first propose a model to describe the problem. Then, an appropriate multi-criteria decision making （MCDM） technique is se- lected to solve it. We ran the model using commercial software such as LINGO~ and then compared the model results to a real case involving one of the largest particleboard manufacturers in the region. The model run based real data yielded a procurement program that is more efficient and lower in cost than the program currently in use. Use of this procurement modelling approach would yield considerable financial returns.

Selecting Best Software Vulnerability Scanner Using Intuitionistic Fuzzy Set TOPSIS

Software developers endeavor to build their products with the least number of bugs.Despite this,many vulnerabilities are detected in software that threatens its integrity.Various automated software i.e.,vulnerability scanners,are available in the market which helps detect and manage vulnerabilities in a computer,application,or a network.Hence,the choice of an appropriate vulnerability scanner is crucial to ensure efficient vulnerability management.The current work serves a dual purpose,first,to identify the key factors which affect the vulnerability discovery process in a network.The second,is to rank the popular vulnerability scanners based on the identified attributes.This will aid the firm in determining the best scanner for them considering multiple aspects.The multi-criterion decision making based ranking approach has been discussed using the Intuitionistic Fuzzy set(IFS)and Technique for Order of Preference by Similarity to Ideal Solution(TOPSIS)to rank the various scanners.Using IFS TOPSIS,the opinion of a whole group could be simultaneously considered in the vulnerability scanner selection.In this study,five popular vulnerability scanners,namely,Nessus,Fsecure Radar,Greenbone,Qualys,and Nexpose have been considered.The inputs of industry specialists i.e.,people who deal in software security and vulnerability management process have been taken for the ranking process.Using the proposed methodology,a hierarchical classification of the various vulnerability scanners could be achieved.The clear enumeration of the steps allows for easy adaptability of the model to varied situations.This study will help product developers become aware of the needs of the market and design better scanners.And from the user’s point of view,it will help the system administrators in deciding which scanner to deploy depending on the company’s needs and preferences.The current work is the first to use a Multi Criterion Group Decision Making technique in vulnerability scanner selection.