Indian Institute of Management Tiruchirappalli

About: Indian Institute of Management Tiruchirappalli is a education organization based out in Tiruchchirappalli, India. It is known for research contribution in the topics: Emerging markets & Context (language use). The organization has 47 authors who have published 105 publications receiving 1694 citations. The organization is also known as: IIM Trichy.

Factors influencing the design of a linear rail network for a dedicated freight corridor

Abstract: The design of a new, linear rail network entails determination of the number and location of sidings in a manner that minimises the total travel times of trains. Given the number of trains that need to be operated and the set of feasible siding locations, we study the influence of the number of siding locations on the travel times of trains along a single track, two-way railway system. For a fixed number of trains that need to be operated, increasing the number of siding locations beyond a critical threshold offsets any incremental ‘meet-pass’ benefits, due to the increased congestion delays incurred by trains at each siding location. A 0–1 mixed integer programme is developed to determine the optimal number of sidings at each location and the best freight train schedule. A computational study on a real world problem is conducted by varying the number of siding locations for different traffic levels. We observe that there exists an optimal number of siding locations for any given traffic level.

Recommendation Engine for Stock Market Trading

Abstract: Investment management is a business problem that is applicable to individuals as well as businesses. Stock market trading can be daunting without the right strategy and tools. Decision making in the stock market is complex as it requires at least some basic understanding of economics, statistics and behavioral science. Due to this, traders face inertia and friction. Automation of the selection of stocks to be considered for trading is an application of computational intelligence, aimed at better discovery of opportunities for buying and selling in a stock market. The automatic selection process to pick stocks from the broad market is something which every trader would desire. In this chapter, a basic stock picking model based on technical analysis strategies is presented. This recommendation engine is proposed with an aim to shift the way one trades by removing some of the biases inherent in the manual process. By employing a few basic technical analysis strategies, the proposed model helps investors discover scrips without performing a detailed study. The resulting baseline list of stocks become choices from which traders can evaluate and determine the actual trades to make. The proposed recommendation engine yields encouraging results, and is practical and easy to implement.

Optimization based on Genetic Algorithm for maintenance decision of multi-unit system

Abstract: Maintenance of equipment is one of the most important operational issues that can be focused on to improve productivity. Maintenance cost includes the cost of preventive and corrective maintenance, which may vary depending on how often maintenance is scheduled. This paper describes the maintenance modeling of a system with multiple parts. The objective is to get a minimum-cost decision that meets the machine availability criteria and to be finished within the time allowed for maintenance. A Genetic Algorithm (GA) is used for the decision parameters optimization. The algorithm procedure leads to a maintenance decision; repair, replacement, or no action for system parts. A case study shows how the model can be used in real life.

Network’s reciprocity: a key determinant of information diffusion over Twitter

Abstract: The role of social media, particularly Twitter, in ensuring the large-scale propagation of information cannot be overemphasised. This study introduces the recipient network’s reciprocity toward a p...