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A new decision model for cross-docking center location in logistics networks under interval-valued intuitionistic fuzzy uncertainty

    Seyed Meysam Mousavi Affiliation
    ; Jurgita Antuchevičienė Affiliation
    ; Edmundas Kazimieras Zavadskas Affiliation
    ; Behnam Vahdani Affiliation
    ; Hassan Hashemi Affiliation

Abstract

Cross-dock has been a novel logistic approach to effectively consolidate and distribute multiple products in logistics networks. Location selection of cross-docking centers is a decision problem under different conflicting criteria. The decision has a vital part in the strategic design of distribution networks in logistics management. Conventional methods for the location selection of cross-docking centers are insufficient for handling uncertainties in Decision-Makers (DMs) or experts’ opinions. This study presents a modern Multi-Criteria Group Decision-Making (MCGDM) model, which applies the concept of compromise solution under uncertainty. To address uncertainty, Interval-Valued Intuitionistic Fuzzy (IVIF) sets are used. In this paper, first an IVIF-weighted arithmetic averaging (IVIF-WAA) operator is used in order to aggregate all IVIF-decision matrices, which were made by a team of the DMs into final IVIF-decision matrix. Then, a new Collective Index (CI) is developed that simultaneously regards distances of cross-docking centers as candidates from the IVIF-ideal points. Finally, the feasibility and practicability of proposed MCGDM model is illustrated with an application example on location choices of cross-docking centers to the logistics network design.

Keyword : multiple cross-docks, location evaluation and selection, logistics networks, multi-criteria decision-making, group decision process, interval-valued intuitionistic fuzzy sets

How to Cite
Mousavi, S. M., Antuchevičienė, J., Zavadskas, E. K., Vahdani, B., & Hashemi, H. (2019). A new decision model for cross-docking center location in logistics networks under interval-valued intuitionistic fuzzy uncertainty. Transport, 34(1), 30-40. https://doi.org/10.3846/transport.2019.7442
Published in Issue
Jan 15, 2019
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