The sand cat swarm optimization (SCSO) is a new heuristic algorithm that simulates the behavior of groups in desert using hearing to hunt. To address shortcomings low accuracy SCSO solution, slow convergence late iterations and easy stagnation, based on stochastic variation elite collaboration (SE-SCSO) was proposed. SE-SCSO first introduces nonlinear periodic adjustment mechanism balance explo...

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 ...

in this paper, a chaotic particle swarm optimization with mutation-based classifier particle swarm optimization is proposed to classifypatterns of different classes in the feature space. the introduced mutation operators and chaotic sequences allows us to overcomethe problem of early convergence into a local minima associated with particle swarm optimization algorithms. that is, the mutationope...

In this paper, Cat Swarm Optimization (CSO) Algorithm is proposed for single stage supply chain distribution system with a fixed cost. This paper considers two kinds of cost: a continuous cost, that linearly increases with the amount transported between a supplier and a customer and a fixed cost, which is incurred whenever a non-zero quantity is transported between a supplier and a customer and...

so far various methods for optimization presented and one of most popular of them are optimization algorithms based on swarm intelligence and also one of most successful of them is particle swarm optimization (pso). prior some efforts by applying fuzzy logic for improving defects of pso such as trapping in local optimums and early convergence has been done. moreover to overcome the problem of i...

Infinite impulse response (IIR) systems are widely used in modeling systems such as communications, bio-systems, acoustics, etc. Many algorithms in computational intelligence area have been developed to identify the systems with a novel search technique, but system identification is challenging due to non-unimodality of the error surface and the non-linear relationship between the error signal ...