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Conference Object Citation - Scopus: 2Evaluation of Partner Companies Based on Fuzzy Inference System for Establishing Virtual Enterprise Consortium(Springer Verlag, 2015) Nikghadam,S.; LotfiSadigh,B.; Ozbayoglu,A.M.; Unver,H.O.; Kilic,S.E.Virtual Enterprise (VE) is one of the growing trends in agile manufacturing concepts. Under this platform companies with different skills and core competences are cooperate with each other in order to accomplish a manufacturing goal. Success of VE, as a consortium, highly depends on the success of its partners. So it is very important to choose the most appropriate companies to enroll in VE. In this study a Fuzzy Inference System (FIS) based approach is developed to evaluate and select the potential enterprises. The evaluation is conducted based on four main criteria; unit price, delivery time, quality and past performance. These criteria are considered as inputs of FIS and specific membership functions are designed for each. By applying fuzzy rules the output of the model, partnership chance, is calculated. In the end, the trustworthy of the model is tested and verified by comparing it with fuzzy-TOPSIS technique providing a sample. © Springer International Publishing Switzerland 2015.Article Citation - WoS: 15Citation - Scopus: 20A Survey of Partner Selection Methodologies for Virtual Enterprises and Development of a Goal Programming-Based Approach(Springer London Ltd, 2016) Nikghadam, Shahrzad; Sadigh, Bahram Lotfi; Ozbayoglu, Ahmet Murat; Unver, Hakki Ozgur; Kilic, Sadik EnginA virtual enterprise (VE) is a platform that enables dynamic collaboration among manufacturers and service providers with complementary capabilities in order to enhance their market competitiveness. The performance of a VE as a system depends highly on the performance of its partner enterprises. Hence, choosing an appropriate methodology for evaluating and selecting partners is a crucial step toward creating a successful VE. In this paper, we begin by presenting an extensive review of articles that address the VE partner selection problem. To fill a significant research gap, we develop a new goal programming (GP)-based approach that can be applied in extreme bidding conditions such as tight delivery timelines for large demand volumes. In this technique, fuzzy analytic hierarchy process (F-AHP) is used to determine customer preferences for four main criteria: proposed unit price, on-time delivery reliability, enterprises' past performance, and service quality. These weights are then incorporated into the GP model to evaluate bidders based on customers' preferences and goals. We present a case study in which we implement the F-AHP-GP technique and verify the model's applicability, as it provides a more flexible platform for matching customers' preferences.
