In this study, the performance of the algorithms of whale, Differential evolutionary, crow search, and Gray Wolf optimization were evaluated to operate the Golestan Dam reservoir with the objective function of meeting downstream water needs. Also, after defining the objective function and its constraints, the convergence degree of the algorithms was compared with each other and with the absolut...

Abstract The feature selection (FS) process has an essential effect in solving many problems such as prediction, regression, and classification to get the optimal solution. For problems, selecting most relevant features of a dataset leads better accuracy with low training time. In this work, hybrid binary crow search algorithm (BCSA) based quasi-oppositional (QO) method is proposed FS on wrappe...

Data clustering is an ideal way of working with a huge amount of data and looking for a structure in the dataset. In other words, clustering is the classification of the same data; the similarity among the data in a cluster is maximum and the similarity among the data in the different clusters is minimal. The innovation of this paper is a clustering method based on the Crow Search Algorithm (CS...

In this paper, single machine scheduling problems with sequence dependent setup times are considered. The objective is to minimize the total weighted tardiness. The single machine total weighted tardiness (SMTWT) scheduling problems with sequence dependent setup times were proved to be strongly NP-hard. A recently developed meta-heuristic algorithm called as crow search algorithm is proposed to...

As a new meta heuristic intelligent algorithm, crow search algorithm simulates the behavior of crows following each other and stealing food. Due to simplicity robustness it has been successfully applied in many fields. However, like swarm intelligence optimization algorithms, also disadvantages slow convergence speed easy fall into local optimization. In order improve accuracy later ability hyb...