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Review Citation - WoS: 18Citation - Scopus: 24A Literature Review on Mhe Selection Problem: Levels, Contexts, and Approaches(Taylor & Francis Ltd, 2015) Saputro, Thomy Eko; Masudin, Ilyas; Rouyendegh (Babek Erdebilli), Babak DaneshvarThis paper presents a review on selection problem of material handling equipment (MHE) and general equipment used in industry area. The issue on MHE is widely paid attention since MHE has contribution on material, good and product accomplishment. Few methods and softwares have been proposed and developed to select the most appropriate MHE for a complex selection problem. Today's high diverisity of MHE categories and types influence the generation of many possible choices which leads to the complexity. In this paper, a further discussion in terms of MHE and equipment including three major points namely level of selection, the context of selection problem and the approaches are served to highlight the complex MHE selection according to the number of possible choices provided, to analyse the consideration for the problem context, and to reveal the superior method for complex MHE selection. Forty-two papers collected from the past study are presented asscociating each point of the discussion.Conference Object Citation - WoS: 69Supplier Selection Using Integrated Fuzzy Topsis and Mcgp: a Case Study(Elsevier Science Bv, 2014) Rouyendegh (Babek Erdebilli), Babak Daneshvar; Saputro, Thomy EkoThis study provides an overview of the fuzzy TOPSIS and Multi-Choice Goal Programming (MCGP) methods for Multi-Criteria Decision-Making (MCDM) problem under uncertain environments. Supplier selection is mostly a complex multi-criteria problem which consists of qualitative and quantitative criteria. Those criteria should be considered advertently as a final decision in comprehensive and objective supplier selection as well. This study deal with the optimum decision making for selecting supplier and allocating order by applying the proposed method of integrated fuzzy TOPSIS and MCGP (Multi-Choice Goal Programming). To deal with the uncertain and imprecise judgment of decision makers, a Fuzzy TOPSIS is utilized to express it by triangular fuzzy numbers. The final supplier selection and order allocation are obtained by integrating the closeness coefficients to the MCGP model. A numerical example is given to clarify the main results developed in this paper. (C) 2013 The Authors. Published by Elsevier Ltd.Article Citation - WoS: 19Citation - Scopus: 21A Hybrid Approach for Selecting Material Handling Equipment in a Warehouse(Taylor & Francis Ltd, 2016) Saputro, Thomy Eko; Rouyendegh (Babek Erdebilli), Babak DaneshvarWarehouse 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.

