Using stigmergy to solve numerical optimization problems
P. Korošec, J. Šilc
Computing and Informatics, 2008, 27(3): 377-402
The current methodology for designing highly efficient technological systems needs to choose the best combination of the parameters that affect the performance. In this paper we propose a promising optimization algorithm, referred to as the Multilevel Ant Stigmergy Algorithm (MASA), which exploits stigmergy in order to optimize multi-parameter functions. We evaluate the performance of the MASA and Differential Evolution---one of the leading stochastic method for numerical optimization---in terms of their applicability as numerical optimization techniques. The comparison is performed using several widely used benchmark functions with added noise.
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