Proceedings of the International Conference on Industrial Engineering and Operations Management Washington DC, USA, September 27-29, 2018 © IEOM Society International A Novel Integrated AHP-TOPSIS Model to Deal with Big Data in Group Decision Making Seyedmohammad Salehi Computer and Information Sciences, University of Delaware, Newark, DE 19716, USA salehi@udel.edu Maghsoud Amiri Department of Industrial Management, Allameh Tabataba’i University, Tehran, Iran amiri@atu.ac.ir Pezhman Ghahremani Department of Industrial & Mechanical Engineering, Islamic Azad University, Qazvin Branch, Qazvin, Iran. pezhman.ghahremani@yahoo.com Mohammadali Abedini Australian Maritime College, University of Tasmania, Launceston, Tasmania 7250, Australia mohammadali.abedinisanigy@utas.edu.au Abstract This study presents an approach for ranking the alternative solutions based on ideal values of criteria. For this purpose, a group multi criteria decision making (GMCDM) model is presented with combination of Analytical Hierarchy Process (AHP) and the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) methods. The proposed model is capable of finding optimal solution for high-dimensional problems with simple and manual calculations. In the first stage, decision making matrix and weight vector of criteria are calculated using AHP, and in the second stage, the alternatives are ranked according to the least distances from ideal values of criteria. The model contributes to the literature by considering intangible and tangible criteria, handling opinions of multiple decision makers, solving problems with many alternatives and criteria in a short time frame, and applying source limitations as spotted to be one of the limitations of decision makers. A numerical example is presented to analyze proposed approach's effectiveness. Findings illustrate that proposed algorithm is flexible against different criteria and is capable to reach similar solutions in comparison with other MCDM methods in a short timeframe and a simplistic approach. Keywords Group Multi Criteria Decision Making (GMCDM); Analytical Hierarchy Process (AHP); Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS); 1. Introduction The growth of competition in today’s business requires successful firms to improve the quality and the quantity of the provided services or products continuously. These improvements require extensive decision makings which include selection of one decision from various alternatives based on different criteria and constraints. The decisions, regardless of their size and time frame, should be managed and handled carefully. According to a recent study, even small decisions and small decision changes can have cascaded impacts on the whole system, causing significant deficiencies (Vahdat, Griffin et al. 2018, Shahraki and Noorossana 2014). In many cases, the final decisions are long-term policies of the companies and may have vital effects on the future of their businesses. Hence, it is important to find methods that reduce the risk of decision making. In the last decades, many researchers have strived to mastermind systematic methods for making risk-free decisions, or decisions with the least affiliated risks and until now, many of these methods have been used in