gravitational search algorithm (gsa) is one of the newest swarm based optimization algorithms, which has been inspired by the newtonian laws of gravity and motion. gsa has empirically shown to be an efficient and robust stochastic search algorithm. since introducing gsa a convergence analysis of this algorithm has not yet been developed. this paper introduces the first attempt to a formal conve...

We propose a new Memetic Particle Swarm Optimization scheme that incorporates local search techniques in the standard Particle Swarm Optimization algorithm, resulting in an efficient and effective optimization method, which is analyzed theoretically. The proposed algorithm is applied to different unconstrained, constrained, minimax and integer programming problems and the obtained results are c...

Abstract— Particle Swarm Optimization (PSO) algorithm is swarm intelligence based algorithm which is used for solving optimization problem. PSO simulates the intelligent foraging behavior of a flock of birds. This paper presents a modification in PSO and develops an algorithm called Highly Convergent Particle Swarm Optimization (HCPSO) algorithm, in which the velocity of particle is made to be ...

This article presents a comparative analysis of the latest swarm-based optimization approaches under partial shading conditions (PSCs) for maximum power point tracking (MPPT) in photovoltaic (PV) systems. The MPPT algorithms are stochastic meta-heuristic that have become very popular recently various applications owing to drawbacks conventional different operating conditions. A comprehensive re...

This paper presents a novel scheduling scheme for the real-time home energy management systems based on Internet of Energy (IoE). The is multi-agent method that considers two chief purposes including user satisfaction and consumption cost. designed under environment microgrid. impact in terms cost savings generally significant system efficiency. That why domestic users are involved appliances. ...

In this paper, a new algorithm which is the result of the combination of cellular learning automata and frog leap algorithm (SFLA) is proposed for optimization in continuous, static environments.At the proposed algorithm, each memeplex of frogs is placed in a cell of cellular learning automata. Learning automata in each cell acts as the brain of memeplex, and will determine the strategy of moti...