Abstract
In this study, a multi-objective model for the reverse logistics network design (RLND) problem and a novel methodology are proposed. The proposed methodology is comprised of two stages: the centralised return centre (CRC) evaluation stage and the reverse logistics network design (RLND) stage. In the first stage an integrated ANP and fuzzy-TOPSIS methodology is utilised. In the second stage, using the CRC weights obtained in the first stage, the RLND model is solved via genetic algorithms (GAs). The proposed methodology is applied to a case from the Turkish white goods industry. The results are discussed and analysed.
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