QoS multicast routing is a non-linear combinatorial optimization problem that arises in many multimedia applications. Providing QoS support is crucial to guarantee effective transportation of multimedia service in multicast communication. Computing the band-widthdelay constrained least cost multicast routing tree is an NP-complete problem. In this paper, a novel heuristic QoS multicast routing ...

In this paper, a hub covering location problem is considered. Hubs, which are the most congested part of a network, are modeled as M/M/C queuing system and located in placeswhere the entrance flows are more than a predetermined value.A fuzzy constraint is considered in order to limit the transportation time between all origin-destination pairs in the network.On modeling, a nonlinear mathematica...

This paper presents Hybrid Particle Swarm Optimization (PSO) Genetic Algorithm (GA) approaches for the document clustering problem. To obtain an optimal solution using Genetic Algorithm, operation such as selection, reproduction, and mutation procedures are used to generate for the next generations. In this case, it is possible to obtain local solution because chromosomes or individuals which h...

Keywords: PSO QPSO Mean best position Weight parameter WQPSO a b s t r a c t Quantum-behaved particle swarm optimization (QPSO) algorithm is a global convergence guaranteed algorithms, which outperforms original PSO in search ability but has fewer parameters to control. In this paper, we propose an improved quantum-behaved particle swarm optimization with weighted mean best position according t...

There are many problems exist in the Evolutionary Algorithm (EA) using Genetic Algorithm (GA), such as slow convergence speed, being easy to fall into the partial optimum ,etc. Particle Swarm Optimization (PSO) can accelerate the space searching and reduce the number of convergences and iterations. The proposed characteristics of Genetic Algorithm Particle Swarm Optimization (GAPSO) are proved ...

A constrained version of the Big Bang-Big Crunch algorithm for the efficient solution of the optimal reservoir operation problems is proposed in this paper. Big Bang-Big Crunch (BB-BC) algorithm is a new meta-heuristic population-based algorithm that relies on one of the theories of the evolution of universe namely, the Big Bang and Big Crunch theory. An improved formulation of the algorithm na...

Integration of Global Positioning System (GPS) and Inertial Navigation System (INS) has been extensively used in aircraft applications like autopilot, to provide better navigation, even in the absence of GPS. Even though Kalman Filter (KF) based GPS/INS integration provides a robust solution to navigation, it requires prior knowledge of the error model of INS, which increases the complexity of ...

This paper presents an enhanced Particle Swarm Optimization (PSO) algorithm applied to the reactive power compensation (RPC) problem. It is based on the combination of Genetic Algorithm (GA) and PSO. Our approach integrates the merits of both genetic algorithms (GAs) and particle swarm optimization (PSO) and it has two characteristic features. Firstly, the algorithm is initialized by a set of a...

This paper presents an optimal design of linear phase digital high pass finite impulse response (FIR) filter using Improved Particle Swarm Optimization (IPSO). In the design process, the filter length, pass band and stop band frequencies, feasible pass band and stop band ripple sizes are specified. FIR filter design is a multi-modal optimization problem. An iterative method is introduced to fin...

In this paper a comparison between the single and multi-objective based Optimization techniques including GA, PSO and Hybrid will be presented. The hybrid technique is combined of two attractive evolutionary techniques, Particle Swarm Optimizer (PSO) and Genetic Algorithm (GA) to enhance the search process by improving the diversity, and the convergence toward the preferred solution. This is no...