The differential ant-stigmergy algorithm: an experimental evaluation and a real-world application

This paper describes the so-called Differential Ant-Stigmergy Algorithm (DASA), which is an extension of the Ant-Colony Optimization for a continuous domain. An experimental evaluation of the DASA on a benchmark suite from CEC 2005 is presented. The DASA is compared with a number of evolutionary optimization algorithms, including the covariance matrix adaptation evolutionary strategy, the differential evolution, the real-coded memetic algorithm, and the continuous estimation of distribution algorithm. The DASA is also compared to some other ant methods for continuous optimization. The experimental results demonstrate the promising performance of the new approach. Besides this experimental work, the DASA was applied to a real-world problem, where the efficiency of the radial impeller of a vacuum cleaner was optimized. As a result the aerodynamic power was increased by twenty per cent.