Optimization algorithms are proposed to tackle different complex problems in different areas. In this paper, we firstly put forward a new memetic evolutionary algorithm, named Monkey King Evolutionary (MKE) Algorithm, for global optimization. Then we make a deep analysis of three update schemes for the proposed algorithm. Finally we give an application of this algorithm to solve least gasoline ...

This paper presents a new multi-objective optimization algorithm in which multi-swarm cooperative strategy is incorporated into particle swarm optimization algorithm, called multi-swarm cooperative multi-objective particle swarm optimizer (MC-MOPSO). This algorithm consists of multiple slave swarms and one master swarm. Each slave swarm is designed to optimize one objective function of the mult...

The optimal power flow issue (OPFI) can be solved in this work using the recently developed algorithm, gorilla troops algorithm (GTA). goal of OPFI is to reduce numerous functions such as minimizing fuel costs, emissions, and losses improving voltage stability related electric networks (EPNs). GTA inspired by gorillas’ social habits, which include migration a strange region, toward specified sp...

Under the background of large-scale and rapid development renewable energy, in order to improve economic benefit system ensure reliability system, this paper introduces hydrogen production energy storage into independent wind/photovoltaic/hydrogen/storage capacity optimization configuration method. In minimize total planning cost self-sufficiency rate power supply, a allocation model was establ...

the objective of this paper is to develop an artificial neural network (ann) model which can beused to predict temperature rise due to climate change in regional scale. in the present work data recorded overyears 1985-2008 have been used at training and testing steps for ann model. the multilayer perceptron(mlp) network architecture is used for this purpose. three applied optimization methods a...

in this paper, we have proposed a new algorithm which combines pso and ga in such a way that the new algorithm is more effective and efficient.the particle swarm optimization (pso) algorithm has shown rapid convergence during the initial stages of a global search but around global optimum, the search process will become very slow. on the other hand, genetic algorithm is very sensitive to the in...