Modern power system networks are operated under highly stressed conditions and there is a risk of voltage instability problems owing to increased load demand. A power system needs to be with sufficient voltage stability margin for secured operation. In this study, SVC parameters of location and size along with generator bus voltages, transformer tap settings are considered as control parameters...

During the history of science of computational, many evolutionary algorithms approaches were proposed having more or less success in solving various optimization problems. The algorithm is applied for numerical simulations based on optimized proportional integral derivative (PID) control of an automatic regulator voltage system for nominal system parameters and step reference voltage input illu...

investment plays a vital role on economic growth. one of the main objectives of all countries is to achieve sustainable economic growth and development. nowadays, a considerable amount of activities performed by the managers and investors in general is to make a portfolio of assets effectively meeting demand goals. in this study, mean-variance markowitz model by cardinality constraints and also...

Reactive power planning is one of the most challenging problem for efficient and source operation of an interconnected power network. It requires effective and optimum co-ordination of all the reactive power sources present in the network. Recently, Teaching Learning Based Optimization (TLBO) algorithm is evolved and finds its application in the field of engineering optimization. In the propose...

A Metaheuristic Optimization is a group of algorithms that are widely studied and employed in the scientific literature. Typically, metaheuristics utilize stochastic operators make each iteration unique, they frequently contain controlling parameters have an impact on convergence process since their impacts mostly neglected most optimization literature, making it difficult to draw conclusions. ...

Dynamic behaviour of a WMN imposes stringent constraints on the routing policy of the network. In the shortest path based routing the shortest paths needs to be evaluated within a given time frame allowed by the WMN dynamics. The exact reasoning based shortest path evaluation methods usually fail to meet this rigid requirement. Thus, requiring some soft computing based approaches which can repl...

One of the most crucial functions in the operation and control of power system is reactive power dispatch (RPD).A hybrid Big Bang–Big Crunch (HBB–BC) optimization algorithm which consists of A Big Bang– Big Crunch algorithm combined with particle swarm optimization (PSO) is proposed in this paper in order to solve optimal reactive power dispatch (ORPD) problem. The L-index of load buses is base...

Due to dynamic network conditions, routing is the most critical part in WMNs and needs to be optimised. The routing strategies developed for WMNs must be efficient to make it an operationally self configurable network. Thus we need to resort to near shortest path evaluation. This lays down the requirement of some soft computing approaches such that a near shortest path is available in an afford...

This paper empirically evaluates four meta-heuristic search techniques namely particle swarm optimization, artificial bee colony algorithm, Genetic Algorithm and Big Bang Big Crunch Algorithm for automatic test data generation for procedure oriented programs using structural symbolic testing method. Test data is generated for each feasible path of the programs. Experiments on ten benchmark prog...