Efficient algorithms for finding maximum matching in graphs
ACM Computing Surveys (CSUR)
Approximation algorithms for scheduling unrelated parallel machines
Mathematical Programming: Series A and B
Exact and approximation algorithms for makespan minimization on unrelated parallel machines
Discrete Applied Mathematics
Improved approximation schemes for scheduling unrelated parallel machines
STOC '99 Proceedings of the thirty-first annual ACM symposium on Theory of computing
Approximation algorithms
Developments from a June 1996 seminar on Online algorithms: the state of the art
Approximation schemes for scheduling and covering on unrelated machines
Theoretical Computer Science
A faster combinatorial approximation algorithm for scheduling unrelated parallel machines
Theoretical Computer Science
On the configuration-LP for scheduling on unrelated machines
ESA'11 Proceedings of the 19th European conference on Algorithms
Selecting a scheduling policy for embedded real-time monitor and control systems
ICESS'04 Proceedings of the First international conference on Embedded Software and Systems
A system for providing differentiated QoS in retail banking
IJCAI'11 Proceedings of the Twenty-Second international joint conference on Artificial Intelligence - Volume Volume Three
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Customers in many developing regions (like India) use physical bank branch as primary and preferred banking channel, resulting in high footfall in the branch. This results in high wait time of customers and high pressure on organization's resources, impacting customer satisfaction (CSAT) as well as employee satisfaction (ESAT) adversely. A naive solution to handle this is to increase the service personnel to cater to the customers. However, this is an unviable alternative because this impacts top and bottom line of the bank. Therefore, organizations are strategically looking for intelligent systems which can help in fine tuning the overall business process to maximize their business objectives while incurring zero or very less investments. Towards this end, we present a system RETRAiN to enable such calibration of various components of bank operations. Based on real time data like waiting customers, service requests, availability of service personnel and business metrics, the system provides recommendations for reconfiguration of the operations. The reconfiguration includes selection of scheduling policy, number of service personnel and configuration of service personnel. We present the overall system along with analysis and optimization algorithms for generating the recommendations. To showcase the efficacy and usefulness of our system, we present results based on data collected over a period of four months from multiple branches of a leading bank in India.