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 proposes a method to solve multi-objective problems using improved particle swarm optimization. we propose leader particles which guide other particles inside the problem domain. two techniques are suggested for selection and deletion of such particles to improve the optimal solutions. the first one is based on the mean of the m optimal particles and the second one is based on appoin...

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...

this paper proposes per unit coding for combined economic emission load dispatch problem. in the proposed coding, it is possible to apply the percent effects of elements in any number and with high accuracy in objective function. in the proposed per unit coding, each function is transformed into per unit form based on its own maximum value and has a value from 0 to 1. in this paper, particle sw...

the present paper aims to investigate the effects of modularity and the layout of subsystems and parts of a complex system on its maintainability. for this purpose, four objective functions have been considered simultaneously: i) maximizing the level of accordance between system design and optimum modularity design,ii) maximizing the level of accessibility and the maintenance space required,iii...

one of the most important applications of multi-objective optimization is adjusting parameters ofpractical engineering problems in order to produce a more desirable outcome. in this paper, the decoupled sliding mode control technique (dsmc) is employed to stabilize an inverted pendulum which is a classic example of inherently unstable systems. furthermore, a new multi-objective particle swarm o...

for multi-objective optimal reactive power dispatch (morpd), a new approach is proposed where simultaneous minimization of the active power transmission loss, the bus voltage deviation and the voltage stability index of a power system are achieved. optimal settings of continuous and discrete control variables (e.g. generator voltages, tap positions of tap changing transformers and the number of...

despite the growing use of evolutionary multi-objective optimization algorithms in different categories of science, these algorithms as a powerful tool in portfolio optimization and specially solving multi-objective portfolio optimization problem is still in its early stages. in this paper, moeas have been used for solving multi-objective portfolio optimization problem in tehran stock market. f...