This paper proposes a new version of the Particle Swarm Optimization (PSO) namely, Modified PSO (MPSO) for model order formulation of Single Input Single Output (SISO) linear time invariant continuous systems. In the General PSO, the movement of a particle is governed by three behaviors namely inertia, cognitive and social. The cognitive behavior helps the particle to remember its previous visi...

This paper proposes a modified particle swarm optimization algorithm (MPSO) to design adaptive neuro-fuzzy controller parameters for controlling the behavior of non-linear dynamical systems. The modification of the proposed algorithm includes adding adaptive weights to the swarm optimization algorithm, which introduces a new update. The proposed MPSO algorithm uses a minimum velocity threshold ...

This paper proposes a modified particle swarm optimization method with non linearly decreasing inertia weight (MPSO-NDIW) and time varying acceleration coefficients. In this MPSO-NDIW method, proper control of the global exploration and local exploitation is done in finding the optimum solution efficiently. In the early stage, full range of search space is allowed for search by the PSO algorith...

Mutative Particle Swarm Optimization (MPSO) is swarm-based stochastic optimization algorithm combined with the mutative function inspired by Genetic Algorithm (GA). The algorithm searches for the solution by combining swarming behavior, as well as mutation of the particles to accelerate the search process. This paper presents a modification to the MPSO algorithm for it to solve Integer Programm...

In this paper, an optimal design of linear phase digital finite impulse response (FIR) filter using Modified Particle Swarm Optimization (MPSO) has been presented. In the design process, the filter length, pass band and stop band frequencies, pass band and stop band ripple sizes are specified. Sometimes the gradient based optimization techniques are not effective for designing filter. An evolut...

A new algorithm based on Modified Particle Swarm Optimization (MPSO) that follows is a local gradient of a chemical concentration within a plume and follows the direction of the wind velocity is investigated. Moreover, the niche or parallel search characteristic is adopted on MPSO to solve the multi-peak and multi-source problem. When using parallel MPSO, subgroup of robot is introduced then ea...

One of the main problems associated with the authoring of e-courses, for e-learning systems, is that the current composition-approaches do not support 'personalized-learning' or in other words, the current composition approaches fail to take into consideration the difference in individual learning-capabilities and the background knowledge of the individual learners and thus do not provide mater...

Particle swarm optimization (PSO) originated from bird flocking models. It has become a popular research field with many successful applications. In this paper, we present a scheme of an aggregate production planning (APP) from a manufacturer of gardening equipment. It is formulated as an integer linear programming model and optimized by PSO. During the course of optimizing the problem, we disc...

This paper develops a new design scheme for the phase response of an all-pass recursive digital filter. A variant of particle swarm optimization (PSO) algorithm will be utilized for solving this kind of filter design problem. It is here called the modified PSO (MPSO) algorithm in which another adjusting factor is more introduced in the velocity updating formula of the algorithm in order to impr...

Particle Swarm Optimization, a recently more popular optimizer utilizes the swarm behavior in searching for an optimum. The classical/standard PSO (SPSO) algorithm is normally used for unconstrained optimization tasks. The Directional Over-Current Relay (DOCR) Coordination problem is a highly constrained optimization problem, therefore the SPSO in its original form cannot be used to solve it. T...