Fuzzy Multi-Criteria Decision-Making Model for Supplier Evaluation and Selection in a Wind Power Plant Project

Wang, Chia–Nan; Yang, Ching-Yu; Cheng, Hung-Chun

doi:10.3390/math7050417

Cited by 32 publications

(15 citation statements)

References 31 publications

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“…Prepare a business process information system evaluation questionnaire. A questionnaire is formed to ask the expected performance of each business process information system with respect to each sub-criterion [48]. Table 2 lists the seven linguistic levels of performance [49].…”

Section: Phase 3: Fuzzy Topsismentioning

confidence: 99%

An Integrated Fuzzy Multi-Criteria Decision-Making Approach for Evaluating Business Process Information Systems

2019

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The prevalence of business-to-business (B2B) has made the relationship among firms more closer than ever. Whether in simple arm-length transactions or business cooperation, many firms, in order to reduce costs and achieve efficiency, have shifted their day-to-day operations from the tradition of relying on manpower to the use of information technology in handling tasks such as inventory, procurement, production planning, distribution, etc. As a result, the need of a business process information system is imminent for firms to coordinate with partners in the supply chain and to be sustainable in the competitive market. This study thus proposes a hybrid multi-criteria decision-making approach for evaluating business process information systems. First, the factors that should be taken into account in selecting an appropriate system are explored. The Decision-Making Trial and Evaluation Laboratory (DEMATEL) is adopted next to understand the interrelationships among the criteria. Based on the results from the DEMATEL, the Fuzzy Analytic Network Process (FANP) is applied to calculate the importance of the factors. Fuzzy Techniques for Order of Preference by Similarity to Ideal Solution (FTOPSIS) is used to rank the business process information systems.The interrelationship among the factors should be considered in the decision-making; thus, the FANP can be a recommended methodology. However, the FANP questionnaire is usually very lengthy and cumbersome. The use of DEMATEL in advance can shorten the questionnaire substantially. FTOPSIS is used to rank the alternatives so that the pairwise comparisons of the alternatives required in the FANP can be avoided. Fuzzy set theory is incorporated in the study so that the uncertainty and ambiguity present in decision-making can be considered. The proposed approach can provide references for decision makers for making relevant decisions and can be revised and adopted in similar problems.Mathematics 2019, 7, 982 2 of 23 of the business process information system can facilitate the business operations within and outside of a firm and to be sustainable in the fierce market. For example, Taiwan Semiconductor Manufacturing Company (TSMC), founded in 1987 in Taiwan, is the largest semiconductor foundry in the world. TSMC, has been implementing the virtual fab concept to provide a wide variety of semiconductor products for customers in the computer, communications, consumer, industrial, and standard semiconductor markets [3]. In order to handle a diversified product portfolio, provide on-time-delivery and short production cycle time, and respond to customer demands spontaneously, TSMC introduced its business process information system in October 1996 and completed its implementation in January 1998. With its successful implementation of the system, the firm can handle its business operations efficiently. In 2017, it manufactured 9920 different products using 258 distinct technologies for 465 different customers [3]. Therefore, if the business process information system can be adopted su...

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Section: Phase 3: Fuzzy Topsismentioning

confidence: 99%

An Integrated Fuzzy Multi-Criteria Decision-Making Approach for Evaluating Business Process Information Systems

2019

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“…When one solution is updated a certain number of times, the quality of its solution has not been improved. At this point, the employed bee will be transformed into a scout bee, and a new honey source will be generated by Formula (21).…”

Section: Artificial Bee Colony Algorithmmentioning

confidence: 99%

“…Zhu and Shi [19] proposed the index system of environmental performance evaluation of energy transition policy, and the comprehensive scoring method was used to evaluate the environmental performance of 2010 and 2015. Gu and Zhang [1] divided energy transition into technology transition and system transition, and the index analysis method was used to measure the degree of energy transition in China, the United States, and Germany.As for evaluation methods, the analytic network process (ANP) [20], fuzzy comprehensive evaluation method [21], data envelopment analysis (DEA) [22], matter element extension method [23], and TOPSIS [24] are widely used in evaluation. However, for complex evaluation problems, the knowledge of experts can be obtained through an intelligence algorithm from traditional evaluation…”

mentioning

confidence: 99%

“…As for evaluation methods, the analytic network process (ANP) [20], fuzzy comprehensive evaluation method [21], data envelopment analysis (DEA) [22], matter element extension method [23], and TOPSIS [24] are widely used in evaluation. However, for complex evaluation problems, the knowledge of experts can be obtained through an intelligence algorithm from traditional evaluation…”

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confidence: 99%

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Performance Evaluation of Energy Transition Based on the Technique for Order Preference by a Similar to Ideal Solution and Support Vector Machine Optimized by an Improved Artificial Bee Colony Algorithm

2019

Energies

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Energy transition is an important factor when dealing with climate change and energy crisis under resource constraints. The performance evaluation of it is significant for improving and promoting the process of energy transition. This paper explores the application of the support vector machine improved by the artificial bee colony algorithm (IABC-SVM) method in the energy transition performance evaluation process. It provides an intelligent evaluation tool for the evaluation of the regional energy transition performance. Firstly, the evaluation indicator system of energy transition is constructed from five dimensions: energy supply, demand, efficiency, institution, and environment. Then, the technique for order preference by a similar to ideal solution improved by a combination weighting (CW-TOPSIS) method and IABC-SVM are constructed. After that, according to the evaluation values of 30 provinces in China calculated by CW-TOPSIS, 10-fold cross validation is used to compare the errors of support vector machine (SVM), support vector machine optimized by the artificial bee colony algorithm (ABC-SVM), and IABC-SVM, which proves the effectiveness and accuracy of IABC-SVM in evaluating the performance of energy transition. Finally, the IABC-SVM is used to evaluate the energy transition performance of 30 provinces in 2016. Through a comparative analysis, the relevant suggestions of energy transition are put forward. Keywords: energy transition; evaluation; the technique for order preference by a similar to ideal solution improved by combination weighting; support vector machine improved by the artificial bee colony algorithm Energies 2019, 12, 3059 2 of 21 and the scientificity of the evaluation method. In recent years, scholars have studied many aspects of energy evaluation, such as energy development evaluation [3][4][5], energy security evaluation [6-10], energy structure evaluation [11][12][13][14], energy efficiency evaluation [15][16][17][18], etc.The evaluation of energy development can also be divided into the evaluation of sustainable energy development, the evaluation and prediction of energy resources, and the evaluation of environmental benefits of energy development. Reference [3] combined the energy demand with the growth rates in various sectors of the economy, formatting standardized data sets, which are used separately by member states of the European community for multi-regional and multi-cycle energy analysis. Li et al. [4] constructed the comprehensive evaluation index of renewable energy from the four aspects of economy, technology, resources, and the environment, and the model of the comprehensive evaluation and structure optimization of renewable energy in China was established. Su et al.[5] evaluated the impact of energy pollution in the whole supply chain from production and transportation to consumer terminals from the perspective of the product life cycle.For the evaluation of energy security, Cherp et al. [6] argued that climate policy can reduce the dependence of the energy supply, energ...

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“…Besides, the FS and its extensions helps to decision-makers to express their opinions by means of linguistic terms. Therefore, more sensitive results can be obtained by applying fuzzy MADM methods to various science and engineering fields such as supplier selection and forecasting [20][21][22][23].…”

Section: Introductionmentioning

confidence: 99%

Some Hesitant Fuzzy Hamacher Power-Aggregation Operators for Multiple-Attribute Decision-Making

Son

Park

2019

Mathematics

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As an extension of the fuzzy set, the hesitant fuzzy set is used to effectively solve the hesitation of decision-makers in group decision-making and to rigorously express the decision information. In this paper, we first introduce some new hesitant fuzzy Hamacher power-aggregation operators for hesitant fuzzy information based on Hamacher t-norm and t-conorm. Some desirable properties of these operators is shown, and the interrelationships between them are given. Furthermore, the relationships between the proposed aggregation operators and the existing hesitant fuzzy power-aggregation operators are discussed. Based on the proposed aggregation operators, we develop a new approach for multiple-attribute decision-making problems. Finally, a practical example is provided to illustrate the effectiveness of the developed approach, and the advantages of our approach are analyzed by comparison with other existing approaches.

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Fuzzy Multi-Criteria Decision-Making Model for Supplier Evaluation and Selection in a Wind Power Plant Project

Cited by 32 publications

References 31 publications

An Integrated Fuzzy Multi-Criteria Decision-Making Approach for Evaluating Business Process Information Systems

An Integrated Fuzzy Multi-Criteria Decision-Making Approach for Evaluating Business Process Information Systems

Performance Evaluation of Energy Transition Based on the Technique for Order Preference by a Similar to Ideal Solution and Support Vector Machine Optimized by an Improved Artificial Bee Colony Algorithm

Some Hesitant Fuzzy Hamacher Power-Aggregation Operators for Multiple-Attribute Decision-Making

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