Support vector machines are trained by solving constrained quadratic optimization problems. This is usually done with an iterative decomposition algorithm operating on a small wor...
We introduce a master–worker framework for parallel global optimization of computationally expensive functions using response surface models. In particular, we parallelize two r...
A Particle Swarm Optimization algorithm with feasibility-based rules (FRPSO) is proposed in this paper to solve mixed-variable optimization problems. An approach to handle various ...
— This paper derives the optimum non-uniform quantization scheme for a distributed estimation problem based on noisy observations in a wireless sensor network. The optimal quanti...
Visvakumar Aravinthan, Sudharman K. Jayaweera, Kos...
Abstract— Memetic algorithms arise as very effective algorithms to obtain reliable and high accurate solutions for complex continuous optimization problems. Nowadays, high dimens...