Cryptanalysis with Computational Intelligence has gained much interest in recent years. This paper presents an approach for breaking the key used in Simplified-Data Encryption Standard (S-DES) using Genetic algorithm (GA), Particle Swarm Optimization (PSO) and a novel approach called Genetic Swarm Optimization (GSO) obtained by combining the effectiveness of GA and PSO. Ciphertext-only attack i...

Intelligent heuristic optimization methods have increasingly attracted the attentions and interests of many scholars in recent years. Such as genetic algorithm, ant colony algorithm, particle swarm optimization, simulated annealing, etc.. They have become effective tools to solve the TSP and other NP-hard combinatorial optimization problems. The particle swarm optimization (PSO) algorithm is a ...

Significant research has been carried out recently to find the optimal path in network routing. Among them, the evolutionary algorithm approach is an area where work is carried out extensively. We in this paper have used particle swarm optimization (PSO) and genetic algorithm (GA) for finding the optimal path and the concept of region based network is introduced along with the use of indirect e...

This paper proposes a novel approach based on the training of the Neural Network method with Particle Swarm Optimization (PSO-NN) for identification of a hydraulic servo robot. The robot is considered to have two degrees of freedom; one is rotational and the other is translational. A feed forward NN is designed for the problem and the weights of the network are trained using Particle Swarm Opti...

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...

The standard Particle Swarm Optimization (PSO) algorithm is a novel evolutionary algorithm in which each particle studies its own previous best solution and the group’s previous best to optimize problems. One problem exists in PSO is its tendency of trapping into local optima. In this paper, a multiple swarms technique(FMSO) based on fast particle swarm optimization(FPSO) algorithm is proposed ...

Particle swarm optimization(PSO) has been applied on feature selection with many improved results. Traditional PSO methods have some drawbacks when dealing with binary space, which may have negative effects on the selection result. In this paper, an algorithm based on fitness proportionate selection binary particle swarm optimization(FPSBPSO) will be discussed in detail aiming to overcome the p...

The reactive power planning and dispatch problems have been solved using Genetic algorithm (GA), Differential evolution (DE) and Particle Swarm Optimization (PSO) technique in order to have a comparative study on the performance of these algorithms. It has been found that Differential evolution performs best followed by the Particle swarm optimization. Both DE and PSO can perform well even with...

This paper demonstrates the application of craziness based particle swarm optimization (CRPSO) technique for designing the 8th order low pass Infinite Impulse Response (IIR) filter. CRPSO, the much improved version of PSO, is a population based global heuristic search algorithm which finds near optimal solution in terms of a set of filter coefficients. Effectiveness of this algorithm is justifi...

This paper proposes an algorithm for Public Key Cryptography (PKC) using the hybrid concept of two evolutionary algorithms, Particle Swarm Optimization (PSO) and Genetic Algorithm (GA) respectively. PSO alone are fast and easy to implement, they follow the procedures of common evolutionary algorithm and posses memory feature which is absent in GA making it more valuable. In GA whole population ...