Multidimensional scalable test functions are very important in testing the capabilities of new optimization methods, especially in evaluating their response to the increase of the search space dimension. As a continuation of a previous published paper, new sets of test functions...
Open access
Research Article10.9734/jamcs/2019/v34i430221
The known gradient descent optimization methods applied to convex functions are using the gradient's magnitude in order to adaptively determine the current step size. The paper is presenting a new heuristic fast gradient descent (HFGD) approach, which uses the change in gradient'...
Open access
Research Article10.9734/JAMCS/2018/39798
In this paper a novel simplified and fast variant of the ABC algorithm is proposed, 1 Population ABC (1P-ABC), with the aim to increase the efficiency of the ABC algorithm by using only one population of bees, the employed bees, while maintaining a good e ectiveness of the algori...
Open access
Research Article10.9734/JAMCS/2017/38065