Exploration and exploitation are two essential components for any optimization algorithm. Much exploration leads to oscillation and premature convergence while too much exploitation slows down the optimization algorithm and the optimizer may be stuck in local minima. Therefore, balancing the rates of exploration and exploitation at the optimization lifetime is a challenge. This study evaluates ...

The effective deployment of electrical energy has received attention because its environmental implications. On the other hand, induction motors are primary equipment used in many industries. Industrial facilities demand maximum percentage energy. This is determined by operating circumstances imposed internal characteristics motor. Because parameters an motor not immediately measurable, they mu...

Influence maximization in a social network refers to the selection of node sets that support fastest and broadest propagation information under chosen transmission model. The efficient identification such influence-maximizing groups is an active area research with diverse practical relevance. Greedy-based methods can provide solutions reliable accuracy, but computational cost required Monte Car...

In this paper, a discrete moth–flame optimization algorithm for community detection (DMFO-CD) is proposed. The representation of solution vectors, initialization, and movement strategy the continuous are purposely adapted in DMFO-CD such that it can solve detection. adaptation, locus-based adjacency used to represent position moths flames, initialization process performed by considering structu...

The performance of photovoltaic (PV) systems is highly dependent on environmental conditions. Due to probable changes in environmental conditions, the real-time control of PV systems is essential for exploiting their maximum possible power. This paper proposes a new method to track the maximum power point of PV systems using the moth-flame optimization algorithm. In this method, the PV DC-DC co...