Using Rough Sets for Optimal Cost Evaluation in Supply Chain Management Shobhit Tiwari Sanjiban Sekhar Roy Madhu Viswanatham V School of Computer Science and School of Computer Science and School of Computer Science and Engineering Engineering Engineering Vellore Institute of Technology Vellore Institute of Technology Vellore Institute of Technology Vellore, India Vellore, India Vellore, India shobhittiwari2008@vit.ac.in sanjibanroy09@gmail.com vmadhuviswanatham@vit.ac.in Abstract—Over the last decade we have seen rapid advancement in the field of rough set theory. It has been successfully been applied to many varied fields such as data mining and network intrusion detection with little or no modifications. The concept of rough set is increasingly becoming popular which can be easily seen from the increasing number of research articles devoted to it. In the past several studies have targeted on finding the qualitative causal relationships that exist between various businesses and their associated attributes. This has resulted in the need for a quantitative approach for the evaluation of cost for supply chain management. However since the process for supply chain management itself depends on multiple complicated features regarding which the standard statistical techniques are not deemed suitable. Therefore in this paper we have analyzed and demonstrated a method for optimal cost evaluation using the rough set theory. Keywords-supply chain management; rough sets; cost evaluation I. INTRODUCTION The change in global macro and micro economic scenario has prompted companies to give more importance to supply chain management. Efficient management of supply chain is important to maintain profitability and business competitiveness. Most business decisions are guided by financial profitability constraints, similarly in the case of supply chain management cost evaluation is a very essential factor to ensure sustainable supply chain management. Cost considerations are more important in case of SME’s which operate on a limited budget. In such cases the profitability of the enterprise greatly depends on analyzing financial aspects of different supply chain management and outsourcing strategies. In this paper we have shed some light on the concepts of rough set theory and later in the paper we have shown how rough set theory can be utilized for cost evaluation in supply chain management. “Fig. 1” shows the conceptual framework of a supply chain for regular business enterprise. II. LITERATURE REVIEW Mentzer et al.[3] defined supply chain management as, ‘‘the systemic, strategic coordination of the traditional business functions and the tactics across these business Figure 1. Conceptual Framework of a Supply Chain. (The dashed line indicates manufacturers who sell directly to final consumers) functions within a particular company and across businesses within the supply chain, for the purposes of improving the long-term performance of the individual companies and the supply chain as a whole’’. In their work Lambert et al. [4] proposed that it refers to ‘‘the integration of key business processes from end-user through original suppliers, that provides products, services, and information that add value for customers and other stakeholders’’. Lindqvist [5] in his work reviewed the research trends in distribution in Finland and discovered that the attributes influencing the length of the distribution channel, the variables accounting for size of retail trade in commune level centres, and the effect of the location and dimension of the automobile dealership on its profitability are at the major factors to be considered in distribution research. While reviewing the existing literature on supply chain management we find that most of them have employed qualitative techniques to examine the causal relationships in supply chain management. These qualitative studies have identified insightful managerial implications for supply chain management. However quantitative methods which provide a more accurate and precise solution to the decision based problem are being developed. While developing algorithms for diagnosing supply chain management, the various Supplier Manufacturer Distributor Customer