An integrated model for supplier selection decisions in configuration changes

Wang, H. S.; H., Z.

doi:10.1016/j.eswa.2006.02.015

Cited by 67 publications

(29 citation statements)

References 7 publications

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“…An AHP methodology [18] based on a combined AHP and a genetic algorithm (GA) also developed. Another integrated model using GA as in [21]. However GA in vendor selection is not much utilised.…”

Section: Literature Surveymentioning

confidence: 99%

Analytic Hierarchy Process (AHP) for a Power Transmission Industry to Vendor Selection Decisions

Kumar¹,

Roy²

2011

IJCA

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This work attempts to develop a rule based model, to evaluate the performance of vendors, supplying components and raw materials to a multinational organization engaged in designing, manufacturing and delivering a range of products covering various stages of electric power transmission and distribution system. The analytic hierarchy process (AHP) based model, described in this work, is utilized to study the requirements of customers to select suitable vendors validate the model for ordering required components and materials for customers.

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Section: Literature Surveymentioning

confidence: 99%

Analytic Hierarchy Process (AHP) for a Power Transmission Industry to Vendor Selection Decisions

Kumar¹,

Roy²

2011

IJCA

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“…Applying FST, T-transformation technology, and genetic algorithms (GA), Wang and Che (2007) developed an integrated model for modelling the change behaviour of product parts, and for evaluating alternative suppliers for each part. Based on the concepts of part change requirements, fuzzy performance indicators, and the integration of different attributes, their model allows the part supplier selection of a specific commercial product to be explored and modelled.…”

Section: Genetic Algorithms Modelsmentioning

confidence: 99%

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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“…Liu et al [8] proposed two modified quality loss functions to measure service quality. Hybrid systems [17][18][19] had been implemented to quantify the attributes like cost, materials, duration and delivery etc. The purchasing department may try to find the optimal supplier not necessarily the supplier offering the best technical service, but also one provides lowest price or the shortest delivery.…”

Section: Literature Surveymentioning

confidence: 99%