Optimizing Generator Selection in Industries Using Shannon Entropy and TOPSIS Method: A New Approach for Intelligent Decision Making

Abstract

Generator selection is one of the key operational tasks in industries, because the production process of companies usually stops during power outages, which can have significant negative effects on production. Therefore, investment in generators is of particular importance. Part of generator selection involves evaluating and ranking different types of generators based on multiple dimensions. The evaluation and selection of generators requires consideration of multiple objectives and criteria, which requires multi-criteria decision-making methods and related analyses. In this study, a multi-criteria decision-making method is presented for ranking and selecting generators in the industry. In this example, the selection of a generator based on four criteria (cost, reliability, spare parts, and reparability) is examined. In this example, three generators are evaluated using Shannon entropy weighting and TOPSIS. The results of the Shannon entropy method show that reparability has the highest weight and reliability has the lowest weight in the generator selection problem. Also, using the TOPSIS technique, we succeeded in selecting a suitable generator for our industry.