Title Development of an integrated decision making model for location selection of logistics centers in the Spanish autonomous communities
Authors YAZDANI, MORTEZA, Chatterjee P. , Pamucar D. , Chakraborty S.
External publication No
Means Expert Syst. Appl.
Scope Article
Nature Científica
JCR Quartile 1
SJR Quartile 1
JCR Impact 6.954
SJR Impact 1.368
Web https://www.scopus.com/inward/record.uri?eid=2-s2.0-85078432901&doi=10.1016%2fj.eswa.2020.113208&partnerID=40&md5=9e92f1b39ba7942ae2a8b6aeda2d9ddf
Publication date 01/01/2020
ISI 000525814900001
Scopus Id 2-s2.0-85078432901
DOI 10.1016/j.eswa.2020.113208
Abstract Logistics centers are those areas where all the national and international logistics and transportation operations are managed and directed to various business operations. One of the essential elements of an urban development system is to identify the appropriate location for a logistics center. In practice, the issue of evaluating and selecting the most suitable geographical area for a logistics center is considered as a complex decision making problem that can be well formulated through analytical and mathematical models. An exhaustive review of literature indicates that no concrete study has still proposed any integrated evaluation approach for logistics center selection. Thus, this paper aims in developing a two-stage decision making model to find out the most preferred zone in the autonomous communities of Spain for establishment of logistics centers. In the first stage, the considered communities are compared based on five evaluation criteria using data envelopment analysis (DEA) to identify the efficient and inefficient alternatives. In the second stage, a model is designed to evaluate the performance of the efficient communities using rough full consistency (R-FUCOM) and combined compromise solution (R-CoCoSo) methods. The adopted model allows capturing the uncertainty and vagueness in the decision makers’ judgments as involved in the evaluation process with the use of rough set theory (RST). The R-FUCOM method is utilized to obtain the optimal weights of the criteria, while R-CoCoSo method is finally used to rank the efficient communities. In addition, sensitivity analyses are performed to validate the robustness of the derived results. © 2020
Keywords Data envelopment analysis; Decision making; Decision theory; International trade; Logistics; Sensitivity analysis; Urban growth; CoCoSo; Decision making models; Evaluation criteria; FUCOM; Integrated
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