Erdebilli, BabekSaputro, Thomy EkoRouyendegh (Babek Erdebilli), Babak DaneshvarIndustrial Engineering2024-07-052024-07-052016171750-96531750-966110.1080/17509653.2015.10425352-s2.0-85015371868https://doi.org/10.1080/17509653.2015.1042535https://hdl.handle.net/20.500.14411/546Erdebilli, Babek/0000-0001-8860-3903; Saputro, Thomy/0000-0002-6148-1130Warehouse operations are closely related to material handling activities. Loading, unloading, transporting and picking material constitute a huge part of the activities. In order to handle material properly as well as to contribute value to the material, the operator and the environment, utilizing Material Handling Equipment (MHE) is required. The selection of proper MHEs requires great focus since its consideration is linked to mutli-criteria and multi-objective decision making problems. Here, a hybrid method is proposed to address the MHE selection problem. An approach that integrates the entropy based hierarchical fuzzy Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) and Multi-Objective Mixed Integer Linear Programming (MOMILP) is used for seeking the best alternative. The evaluation of alternatives is performed based on both subjective and objective criteria. Subjective weights are derived from a fuzzy Analytic Hierarchy Process (AHP). To deal with objective criteria, the entropy method is adopted to determine the weights, and the integrated weights are also calculated. The alternatives are rated by using fuzzy TOPSIS. For final execution of the selection, an MOMILP model is developed incorporating two goals, namely to minimize the disadvantage of material handling operation and to minimize the total cost of material handling. The AUGMented E-CONtraint method (AUGMECON) is used to solve the model. A case study is given to illustrate the method. The results show the effectiveness of the hybrid method in complex decision making.eninfo:eu-repo/semantics/openAccessMHE selectionwarehouse operationsMCDMfuzzy logicMOMILPArticleQ11113448WOS:000376238600004