A methodology for selection problems with multiple, conflicting objectives and both qualitative and quantitative criteria

Erol, İsmail; Ferrell, William G.

doi:10.1016/s0925-5273(03)00049-5

Cited by 116 publications

(53 citation statements)

References 22 publications

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“…Subsequently, many fuzzy based models/methods have been utilised for partner selection in supply chain management, as discussed in the four sub-sections above. Besides the above fuzzy based approaches, Erol and Ferrell (2003) also used fuzzy quality function deployment (QFD) to convert qualitative information into quantitative parameters and then combined this data with other quantitative data to parameterize a multi-objective mathematical programming model. Bevilacqua et al, (2006) proposed a fuzzy QFD approach to support supply partner selection.…”

Section: Summary Of Literature Reviewmentioning

confidence: 99%

“…In this paper, we use triangular membership function as shown in Figure 3. The intervals associated with different linguistic variables may overlap to reflect the existence of inherent fuzziness of adjacent words such as high and very high (Erol andFerrell, 2003, Famuyiwa et al, 2008). As the simplicity of triangular membership function, the fuzzy intelligent model uses it to measure the degree of membership of each linguistic level relative to the rating scale of 1-10.…”

Section: Fuzzification Of Linguistic Variablesmentioning

confidence: 99%

“…Furthermore, the decision sometimes involves much complex and imprecise information about potential partners, especially during the early stage of the process (Famuyiwa et al, 2008;Wu and Barnes, 2011). In these cases, FST is one of the best tools to handle uncertainty (Erol and Ferrell 2003;Yucel and Guneri, 2011).…”

Section: Introductionmentioning

confidence: 99%

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Partner selection in agile supply chains: a fuzzy intelligent approach

Barnes

2013

Production Planning & Control

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-2 - Partner selection in agile supply chains: a fuzzy intelligent approachPartner selection is a fundamental issue in supply chain management as it contributes significantly to overall supply chain performance. However, such decision making is problematic due to the need to consider both tangible and intangible factors, which cause vagueness, ambiguity and complexity. This paper proposes a new fuzzy intelligent approach for partner selection in agile supply chains (ASC) by using fuzzy set theory in combination with radial basis function artificial neural network. Using these two approaches in combination enables the model to classify potential partners in the qualification phase of partner selection efficiently and effectively using very large amounts of both qualitative and quantitative data. The paper includes a worked empirical application of the model with data from eighty-four representative companies within the Chinese electrical components and equipment industry, to demonstrate its suitability for helping organizational decision makers in partner selection.

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Section: Summary Of Literature Reviewmentioning

confidence: 99%

Section: Fuzzification Of Linguistic Variablesmentioning

confidence: 99%

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Partner selection in agile supply chains: a fuzzy intelligent approach

Barnes

2013

Production Planning & Control

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“…De Boer et al (2001) by providing a comprehensive review of the supplier selection's literature proposed the fuzzy set theory as a way for improving the vendor selection process. In addition, to find the supplier with the best overall performance rating among suppliers, Erol et al (2003) discussed the advantages of fuzzy set theory in supplier selection issues. Also recently Kumar et al (2004) have applied a fuzzy goal programming approach for solving the vendor selection problem in supply chain providing a decision method for handle the vagueness and imprecision objectives.…”

Section: Introductionmentioning

confidence: 99%

An Integrated Hybrid MCDM Approach for Vendor Selection Problem (Case Study: Iran Khodro)

Kassaee¹,

Farrokh²,

Nia³

2013

BMH

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Vendor selection is an important issue in most company based on many criteria that includes ambiguous or uncertain data. Therefore in the study, it is essential that fuzzy approach is employed for coping with the uncertainty and achieving more accurate results. In other hand, the relationships between criteria and sub-criteria are complex; for encompassing the complexity, most conventional decision models cannot help us explain the interrelationships among the criteria. In this paper, a hybrid multi-criteria decision making (MCDM) technique is proposed to determine the structural relationships and the interrelationships among all the evaluation's dimensions based the Analytic Network Process (ANP) method determining appropriate weightings to each sub-criterion. Then alternatives priority should be determined which can aid the decision making. For the purpose, The TOPSIS (technique for order performance by similarity to idea solution) is used to rank all competing alternatives in terms of their overall performances. In MCDM studies and research, applying TOPSIS in ranking alternatives has recently been customary because of its advantages. In the end, a case study of an Iranian company, in automotive industry, is demonstrated to illustrate the proposed model can improve solving of vendor selection problem.

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“…Using fuzzy concepts leads to more flexible, responsive and robust environment in supply chain which can handle changes more easily and cope with them naturally. Erol & Ferrel (2003) discussed applications of fuzzy set theory in finding the supplier with the best overall rating amomg suppliers. Fazel Zarandi & Saghiri (2006) presented a fuzzy expert system model for SC complex problems.…”

mentioning

confidence: 99%