We propose a framework which we call stochastic offline programming (SOP). The idea is to embed the development of combinatorial algorithms in an off-line learning environment whi...
Energy-efficiency has been an important system issue in hardware and software designs to extend operation duration or cut power bills. This research explores systems with probabil...
—Differential evolution (DE) is arguably one of the most powerful stochastic real-parameter optimization algorithms in current use. DE operates through similar computational step...
We present a probabilistic analysis for a large class of combinatorial optimization problems containing, e.g., all binary optimization problems defined by linear constraints and a...
The problem of finding an optimal bipartition of a rectangle set has a direct impact on query performance of dynamic R-trees. During update operations, overflowed nodes need to be...