Backtracking search optimisation algorithm (BSA) is a commonly used meta-heuristic
optimisation algorithm and was proposed by Civicioglu in 2013. When it was first used, it …

Obtaining appropriate parameters of photovoltaic models based on measured current-
voltage data is crucial for the evaluation, control, and optimization of photovoltaic systems …

The distributed assembly flow shop scheduling problem (DAFSP) is an important scenario in
manufacturing system. In this paper, an optimal block knowledge driven backtracking search …

Evolutionary algorithms (EAs) have a lot of potential to handle nonlinear and non-convex
objective functions. Particularly, the backtracking search algorithm (BSA) is a popular nature …

In this paper, a new multi-objective approach is suggested, known as multi-objective
backtracking search algorithm (MOBSA) in order to formulate and solve the optimal power …

For the synchronization and control of fractional-order chaotic systems, knowing parameters
and orders is essential as well as being a hot topic. In this paper, the problem of parameters …

Prediction of nonlinear and dynamic systems is a challenging task, however with the aid of
machine learning techniques, particularly neural networks, is now possible to accomplish …

Surrogate models have been radically used in metaheuristic algorithms owing to their
capacity in solving computationally expensive problems. However, despite the promising …

Recently, an effective method called return maps is proposed for the parameter estimation of
chaotic systems. However, high time-consumption limits practical applications. In this paper …

To improve the performance of the backtracking search optimization algorithm (BSA), a multi-
population cooperative evolution strategy guided BSA with hierarchical knowledge (HKBSA) …