Enabling weakened hedges in linguistic multi-criteria decision making

A semantics-based model is proposed to enable weakened hedges, such as ＂more or less＂ and ＂roughly＂ in the context of linguistic multi-criteria decision making. First, the resemblance relations are defined based on the semantics of terms on the domain. Then, the hedges can be represented after the upper and loose upper approximations of a linguistic term are derived. Accordingly, some compact formulae can be derived for the semantics of linguistic expressions with hedges. Parameters in these formulae are objectively determined according to the semantics of original terms. The proposed model presents a more natural way to express the decision information under uncertainties and its semantics is clear. The proposed model is clarified by solving the problem of evaluation and selection of sustainable innovative energy technologies. Computational results demonstrate that the model can deal with various uncertainties of the problem. Finally, the model is compared with existing techniques and extended to the case when the semantics of terms are represented by trapezoidal fuzzy numbers.

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.

The Development of the Generation Expansion Planning System Using Multi-Criteria Decision Making Rule

The power expansion planning is large and capital intensive capacity planning. In the past, the expansion planning was established with the proper supply reliability in order to minimize social cost. However, such planning cannot be used in the power markets with many market participants. This paper proposed the power expansion planning process in the power markets. This system is composed of Regulator and Generation Company （GENCO）＇s model. Multi-criteria decision making rule is used for regulator model and several scenarios for GENCO model are applied.

Decision making tools for optimal material selection:A review

The present work reviews different decision making tools(material comparing and choosing tools)used for selecting the best material considering different parameters.In this review work,the authors have tried to address the following important enquiries:1)the engineering applications addressed by the different material choosing and ranking methods;2)the predominantly used decision making tools addressing the optimal material selection for the engineering applications;3)merits and demerits of decision making tools used;4)the dominantly used criteria or objectives considered while selecting a suitable alternative material;5)overview of DEA on material selection field.The authors have surveyed literatures from different regions of the globe and considered literatures since 1988.The present review not only stresses the importance of material selection in the early design stage of the product development but also aids the design and material engineers to apply different decision making tools systematically.

Application of TOPSIS Method in Support of Decisions Made in Staff Management Issues

Evaluation model was proposed which refers to fuzzy formalism of the personnel management issues taking account their specific characteristics. Application of TOPSIS （technique for order Performance by similarity to ideal solution） method for evaluation and regulation of alternatives based on hierarchically structured criteria of qualitative character by multiple experts to intellectually support decisions made in staff management issues is reviewed in the article. Candidate selection experiment based on criteria system formed using TOPSIS method for evaluation of candidates during solution of hiring problems reviewed and obtained results were compared with results obtained using Matlab program package.

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.

An Evaluation of the Critical Success Factors in Sustainable Food Supply Chains in Developing Countries

Food is one of the biggest industries in developed and underdeveloped countries. Supply chain sustainability is essential in established and emerging economies because of the rising acceptance of cost-based outsourcing and the growing technological, social, and environmental concerns. The food business faces serious sustainability and growth challenges in developing countries. A comprehensive analysis of the critical success factors (CSFs) influencing the performance outcome and the sustainable supply chain management (SSCM) process. A theoretical framework is established to explain how they are used to examine the organizational aspect of the food supply chain life cycle analysis. This study examined the CSFs and revealed the relationships between them using a methodology that included a review of literature, interpretative structural modeling (ISM), and cross-impact matrix multiplication applied in classification (MICMAC) tool analysis of soil liquefaction factors. The findings of this research demonstrate that the quality and safety of food are important factors and have a direct effect on other factors. To make sustainable food supply chain management more adequate, legislators, managers, and experts need to pay attention to this factor. In this work. It also shows that companies aiming to create a sustainable business model must make sustainability a fundamental tenet of their organization. Practitioners and managers may devise effective long-term plans for establishing a sustainable food supply chain utilizing the recommended methodology.

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.

Mineral processing plant location using the analytic hierarchy process——a case study:the Sangan iron ore mine(phase 1)

Locating the mineral processing plant near a mine is the most important parameter that affects the whole process.Many factors,and their preferences,should be considered in this stage.The factors include economical,geological,technical,environmental and tectonic parameters.A multi-criteria decision making method is necessary to rank the alternatives.In this paper we describe how plant location is selected by using the Analytic Hierarchy Process(AHP).This method,with eight criteria,was used to select a location for the mineral processing plant at the Sangan iron ore mine(phase 1).Three alternatives for the processing plant were evaluated.The main criteria were distance from the mine,access to heavy machinery transport,the amount of excavation required for grading,bed mixture capacity,belt conveyor length,distance from the tailing dam,distance from the waste dumps and surface water diversion requirements.Finally,the alternatives were ranked and the best location was proposed.