In this study, a new method for designing the damping controller was proposed to improve the transient power system stability in a single machine network connected to an infinite bus. The STATCOM controller problem in a wide area of the system function was considered as an optimization problem with multi-purpose objective function. Also, the Honey Bee Mating Optimization Algorithm was used to d...

This paper addresses the underlying principles of Evolvable Assembly Systems. This paradigm was recently proposed as an answer to the requirements faced by assembly companies in the current world of business and technological change.i. The basis for this new approach lies in a muhi-disciplinary study of the needs and requirements, and shifts the technological focus from complex, flexible, multi...

Purpose – The purpose of this paper is threefold: to make explicitly clear the range of efficient multi-objective optimization algorithms which are available with kriging; to demonstrate a previously uninvestigated algorithm on an electromagnetic design problem; and to identify algorithms particularly worthy of investigation in this field. Design/methodology/approach – The paper concentrates ex...

in this study, under the constraint of resource-saving and environment-friendliness objective, based on multi-agent genetic algorithm, multi-objective spatial optimization (moso) model for land use allocation was developed from the view of simulating the biological autonomous adaptability to environment and the competitive-cooperative relationship. the model was applied to solve the practical m...

in this paper, we proposed an algorithm for solving the problem of task scheduling using particle swarm optimization algorithm, with changes in the selection and removing the guide and also using the technique to get away from the bad, to move away from local extreme and diversity. scheduling algorithms play an important role in grid computing, parallel tasks scheduling and sending them to appr...

numerous problems encountered in real life cannot be actually formulated as a single objective problem; hence the requirement of multi-objective optimization (moo) had arisen several years ago. due to the complexities in such type of problems powerful heuristic techniques were needed, which has been strongly satisfied by swarm intelligence (si) techniques. particle swarm optimization (pso) has ...

this paper explores the capabilities of multi-objective particle swarm optimization algorithmin a simulation-optimization model for solving waste load allocation problems. the main goals are totaltreatment costs, violation of the water quality standards and equity. in this research, the water qualitysimulation model is coupled with a multi-objective optimization model, mopso. in order to derive...

through a collection of cooperative agents called ants, the near optimal solution to the multi-reservoir operation problem may be effectively achieved employing ant colony optimization algorithms (acoas). the problem is approached by considering a finite operating horizon, classifying the possible releases from the reservoir(s) into pre-determined intervals, and projecting the problem on a grap...