Algorithms and Optimization
At XRCI, the vision of the Algorithms and Optimization research area is to develop novel and efficient algorithmic solutions for various optimization problems that arise from the Xerox Services and Technology business. Area members have technical expertise in a variety of topics including mechanism design, game theory, distributed algorithms, stochastic optimization, scheduling, graph algorithms, and business process analytics and optimization.
Research activities in the area are targeted towards various Xerox business domains, which include transportation, enterprise print services, and HR services. The team’s focus is to develop new and efficient algorithmic solutions to solve problems that arise in fields such as urban mobility, print shop management, talent management, business process analytics, and human computation
The project focuses on optimizing transportation services domain for emerging markets and worldwide.
One of the major focus points is a novel integration of unscheduled on-demand transportation services with scheduled transportation services for multi-modal trip planning. This involves designing routing and pricing solutions for effective ride sharing. The research challenges include the classical Dial-a-Ride and other vehicle routing problems as well as in designing real-time effective solutions that are acceptable to both commuters and service providers.
Another focus area is in designing demand-driven optimal routing and scheduling algorithms for public transportation. This involves designing new techniques and adapting conventional solutions in order to address emerging market issues such as large and variable demand, demand-supply imbalance, variable environment, traffic congestion etc., which present new research challenges.
This project focuses on the print technology domain to analyze and optimize print shop productivity. It tries to analyze historical event data pertaining to print processes and identify bottlenecks and scope for optimization. The project addresses challenges in geographically distributed and multi-site service operations, such as planning and scheduling, which are very different from stand-alone print shops.
This project aims to build a next-generation platform for talent management. The project focuses on two key aspects of talent management — talent acquisition and workforce optimization. In talent acquisition, the project team is building a solution for screening and interviewing candidates from a large candidate pool. The workforce optimization solution addresses capacity planning and project staffing problems in a modern service delivery organization.