As IT investments focus more and more on cost reductions, enterprises are seeking more advanced and strategic use of computer systems through data analytics and optimization technologies based on sophisticated mathematical models. TRL has world-class researchers in applied mathematics, especially in the field of data analytics, machine learning, and optimization. Through collaboration with clients, these technologies have had a great impact on real-world problems, such as optimization in steel mill plants.
Competency fields
Optimization
We are researching optimization algorithms, such as how to find the optimal ordering, combinations, assignments, and packing, which are required for various business problems in several industries such as manufacturing, distribution, and the public sector. Examples of optimi-zation problems we have tackled include printed-circuit-board drilling, truck routing, multi-modal less-than-truckload network design, warehouse location planning, free-form nesting, nurse scheduling, crew scheduling,inventory applications, and end-to-end scheduling in steel mills.
Data Analytics
Our research focus is on methodologies and frameworks for deriving insights into businesses and services from the huge volumes of data now available from maturing IT infrastructures, and linking these insights to actions. We are studying fundamental analysis methods such as anomaly detection and risk-sensitive data analytics, and also obtaining many results by applying these methods to time series data in manu-facturing and CRM data, leveraging the merits of our proximity to advanced companies and markets in Japan.
Text Mining
Text Mining extracts human intentions and sentiments from written text and reveals hidden tendencies and correlations among the concepts in text. Such features are hard to detect manually. We have developed two solution systems. One is a text mining system called TAKMI, used for problem recognition, FAQ creation, finding potential customers, etc., based on voice of the customers (VOC) analysis of call center logs. The other is a sentiment analysis system, used for extracting and analyzing positive or negative comments within texts (such as questionnaires) for rapid user feedback to product and service development teams.
Discrete Algorithm
We study algorithms for various discrete problems. Many optimization problems, such as truck routing and scheduling, are discrete problems, and they may involve more general discrete problems as their components, such as set covering or matching problems. We study the development of discrete algorithms for these problems, by leveraging various methods to solve the subproblems or by devising efficient data structures. We also study methods to evaluate discrete systems whose inputs vary stochastically.
Text Processing Assistance Tool
Document processing is inevitable in enterprises, and high-quality documents are required for customers. In addition, globalization is greatly increasing the demands for translations. We have been working on the research and development of tools to address document processing needs such as critiquing, translating, and sanitizing or masking.
