Multi objective (MO) optimization is an emerging field which is increasingly being implemented in many industries globally. In this work, the MO optimization of the extraction process of bioactive compounds from the Gardenia Jasminoides Ellis fruit was solved. Three swarm-based algorithms have been applied in conjunction with normal-boundary intersection (NBI) method to solve this MO problem. T...

The controller area network (CAN) bus has become one of the most commonly used protocols in automotive networks. Some potential attackers inject malicious data packets into CAN through external interfaces for implementing illegal operations (intrusion). Anomaly detection is a technique intrusion which can detect packs by comparing normal with incoming obtained from traffic. symmetric and stable...

Unlike all recent research which used Concentric Circular Antenna Array (CCAA) based on one beam-former for each single main beam, this research presents a technique to adapt smart CCAA by using only single beam-former for multi main beams based on hybrid PSOGSA. Hybrid PSOGSA is a combining technique between Particle Swarm Optimization and Gravitational Search Algorithm which is applied in the...

The automatic load frequency control for multi-area power systems has been a challenging task system engineers. complexity of this further increases with the incorporation multiple sources generation. For multi-source system, paper presents new heuristic-based hybrid optimization technique to achieve objective control. In particular, proposed regulates deviation and tie-line in system. uses mai...

This work proposes a new meta-heuristic called Grey Wolf Optimizer (GWO) inspired by grey wolves (Canis lupus). The GWO algorithm mimics the leadership hierarchy and hunting mechanism of grey wolves in nature. Four types of grey wolves such as alpha, beta, delta, and omega are employed for simulating the leadership hierarchy. In addition, the three main steps of hunting, searching for prey, enc...

this paper proposes the exchange market algorithm (ema) to solve the combined economic and emission dispatch (ceed) problems in thermal power plants. the ema is a new, robust and efficient algorithm to exploit the global optimum point in optimization problems. existence of two seeking operators in ema provides a high ability in exploiting global optimum point. in order to show the capabilities ...

Meta-heuristic search algorithms are developed to solve optimization problems. Such algorithms are appropriate for global searches because of their global exploration and local exploitation abilities. Swarm intelligence (SI) algorithms comprise a branch of meta-heuristic algorithms that imitate the behavior of insects, birds, fishes, and other natural phenomena to find solutions for complex opt...

Random deployment of sensor nodes is susceptible to initial communication hole, even when the network is densely populated. However, eliminating holes using structural deployment poses its difficulties. In either case, the resulting coverage holes can degrade overall network performance and lifetime. Many solutions utilizing Relay Nodes (RNs) have been proposed to alleviate this problem. In thi...

With the increasing power demand, voltage fluctuations are to be controlled for a reliable and stable power system. On the same way voltage fluctuations create reactive power mismatch in the system. To overcome these conditions we have to perform reactive power optimisation that would balance the reactive power flow of the system. There are several methods and algorithms that serve best for thi...