A new integrated grey mcdm model : Case of warehouse location selection
Date
2021Metadata
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Ulutaş, A., Balo, F., Sua, L., Demir, E., Topal, A., & Jakovljević, V. (2021). A new integrated grey mcdm model: case of warehouse location selection. Facta Universitatis, Series: Mechanical Engineering, 19(3), p. 515-535.Abstract
Warehouses link suppliers and customers throughout the entire supply chain.
The location of the warehouse has a significant impact on the logistics process. Even
though all other warehouse activities are successful, if the product dispatched from the
warehouse fails to meet the customer needs in time, the company may face with the risk
of losing customers. This affects the performance of the whole supply chain therefore the
choice of warehouse location is an important decision problem. This problem is a multicriteria decision-making (MCDM) problem since it involves many criteria and
alternatives in the selection process. This study proposes an integrated grey MCDM
model including grey preference selection index (GPSI) and grey proximity indexed value
(GPIV) to determine the most appropriate warehouse location for a supermarket. This
study aims to make three contributions to the literature. PSI and PIV methods combined
with grey theory will be introduced for the first time in the literature. In addition, GPSI
and GPIV methods will be combined and used to select the best warehouse location. In
this study, the performances of five warehouse location alternatives were assessed with
twelve criteria. Location 4 is found as the best alternative in GPIV. The GPIV results
were compared with other grey MCDM methods, and it was found that GPIV method is
reliable. It has been determined from the sensitivity analysis that the change in criteria
weights causes a change in the ranking of the locations therefore GPIV method was found
to be sensitive to the change in criteria weights