A new meta-heuristic optimization technique: a sensory-deprived optimization algorithm
Fahad S. Abu-Mouti, M.E. El-Hawary · 2010
This paper presents a new and efficient metaheuristic optimization algorithm inspired by the intelligent behavior/survival of sensory-deprived human beings. The proposed algorithm (SDOA) is a population-based with distinct features occurring at the semi-exploration and semi-exploitation tactical levels. The performance of the proposed algorithm is assessed utilizing a set of benchmark optimization functions. In addition, a comparison of the results obtained by the proposed algorithm with those found using other well-known algorithms is conducted. The efficiency of the proposed SDOA is confirmed by the fact that the standard deviation of the results obtained for 30 independent runs is virtually zero.