This article proposes an effective evolutionary hybrid optimization method for identifying unknown parameters in photovoltaic (PV) models based on the northern goshawk algorithm (NGO) and pattern search (PS). The chaotic sequence is used to improve exploration capability of NGO technique while evading premature convergence. suggested algorithm, goshawk, (CNGPS), takes advantage algorithm’s glob...

In this paper an integrated lot-sizing and scheduling problem in a flexible job shop environment with machine-capacity-constraint is studied. The main objective is to minimize the total cost which includes the inventory costs, production costs and the costs of machine’s idle times. First, a new mixed integer programming model,with small bucket time approach,based onProportional Lot sizing and S...

There have been several researches of applying Deep Belief Networks (DBNs) to predict time series data. Most these works pointed out that DBNs can bring better prediction accuracy than traditional Artificial Neural Networks. However, one the main shortcomings using in concerns with proper selection their parameters. In this paper, we investigate use Harmony Search algorithm for determining para...

Despite the good performance of Crow Search Algorithm (CSA) in dealing with global optimization problems, unfortunately it is not case respect to convergence performance. Conventional CSA exploration and exploitation are strongly dependent on proper setting awareness probability (AP) flight length (FL) parameters. In each problem, AP FL parameters set an ad hoc manner their values do change ove...