Search

Combined heat and power systems are known for their high efficiency. On the other hand, economic dispatching of these systems is very important in terms of total efficiency and reliability of the power system. The novelty of this study is to use the Filled Function Method (FFM) to solve this optimization problem in a way different from that to be found in the literature. Moreover, the Taguchi method is combined with the FFM for the first time to obtain the best initial parameters. So the proposed hybrid deterministic optimization algorithm is called the Taguchi-based Filled Function Method (TFFM). The most important advantage of the suggested TFFM is that it always gives the same result for the same inputs and all the solutions are in the feasible region. The method is applied to four different test systems and the results obtained are compared with those of recent powerful optimization algorithms. With the proposed optimization method, a significant performance increase of 5.676% was achieved. Online supplemental data for this article can be accessed at https://doi.org/10.1080/0305215X.2022.2034802. [ABSTRACT FROM AUTHOR]

In this paper, a novel hybrid Taguchi-vortex search algorithm (HTVS) is proposed for solving global optimization problems. Taguchi orthogonal approximation and vortex search algorithm (VS) are hybridized in presenting method. In HTVS, orthogonal arrays in the Taguchi method are trained and obtained better solutions are used to find global optima in VS. Thus, HTVS has better relation between exploration and exploitation, and it exhibits more powerful approximation to find global optimum value. Proposed HTVS algorithm is applied to sixteen well-known benchmark optimization test functions with different dimensions. The results are compared with the Taguchi orthogonal array approximation (TOAA), vortex search algorithm, grey wolf optimizer (GWO), sine cosine algorithm (SCA), moth-flame optimization algorithm (MFO), whale optimization algorithm (WOA) and salp swarm algorithm (SSA). In order to compare the effectiveness of HTVS statistically, Wilcoxon signed-rank test (WSRT) is used in this study. Furthermore, HTVS is applied to two different real engineering problems having some constraints (tension/compression spring design and pressure vessel design). All obtained results suggested that HTVS can find optimal or very close to optimal results. Moreover, it has good computational ability and fast convergence behavior as well. [ABSTRACT FROM AUTHOR]