Intensity-modulated radiation therapy (IMRT) allows for the design of customized, highly-conformal treatments cancer patients. Creating IMRT treatment plans, however, is a mathematically complex process, which often tackled in multiple, simpler stages. This sequential approach typically separates dose requirements from mechanical deliverability considerations, may result suboptimal quality. For...

Robust optimization can provide safe and tractable analytical approximation for the chance constrained optimization problem. In this work, we studied the application of robust optimization approximation in solving chance constrained planning and scheduling problem under uncertainty. Four different robust optimization approximation methods for improving the quality of robust solution were invest...

We give an overview of a new set of learningbased algorithms for fast and robust motion planning with noisy sensor data. These include improved search in configuration spaces using instance-based learning, and robust proximity queries in configuration spaces with noisy data. We demonstrate the performance of these new proximity and planning algorithms on the PR2 robot with noisy point-cloud data.

Intensified industrialization in developing countries has recently resulted in huge electric power demand growth; however, electricity generation in these countries is still heavily reliant on inefficient and traditional non-renewable technologies. In this paper, we develop an integrated game-theoretic model for effective power systems planning thorough balancing between supply and demand for e...

Lean manufacturing is a strategic concern for companies which conduct mass production and it has become even more significant for those producing in a project-oriented way by modularization.  In this paper, a bi-objective optimization model is proposed to design and plan a supply chain up to the final assembly centre. The delivery time and the quality in the procurement and low fluctuation of t...