Inspired by the evolution process of human intelligence and the social learning theory, a new swarm intelligence algorithm paradigm named the social learning optimization (SLO) algorithm is proposed. SLO consists of three co-evolution spaces: the bottom is the micro-space, where genetic evolution occurs; the middle layer is the learning space, where individuals enhance their intelligence throug...

Swarm robots are special multi-robots and usually considered being controlled with swarm intelligence-basedmethod to complete some assigned complex tasks (Dorigo and Sahin, 2004). Similar to the biological counterparts in nature, swarm intelligence among such artificial system is emerged from local interactions between individual robots or individual robot and its environment (Beni, 2005; Şahin...

Abstract— Particle Swarm Optimization (PSO) algorithm is swarm intelligence based algorithm which is used for solving optimization problem. PSO simulates the intelligent foraging behavior of a flock of birds. This paper presents a modification in PSO and develops an algorithm called Highly Convergent Particle Swarm Optimization (HCPSO) algorithm, in which the velocity of particle is made to be ...

Partitioning is a fundamental problem in diverse fields of study such as VLSI design, parallel processing, data mining and task scheduling. The min-cut bipartitioning problem is a fundamental graph partitioning problem and is NP-Complete. In this paper, we present an effective multi-level refinement algorithm based on swarm intelligence for bisecting graph. The success of our algorithm relies o...

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...

The vehicle routing problem VRP is a well-known combinatorial optimization problem. It has been studied for several decades because finding effective vehicle routes is an important issue of logistic management. This paper proposes a new hybrid algorithm based on two main swarm intelligence SI approaches, ant colony optimization ACO and particle swarm optimization PSO , for solving capacitated v...

We present an algorithm that is inspired by theoretical and empirical results in social learning and swarm intelligence research. The algorithm is based on a framework that we call incremental social learning. In practical terms, the algorithm is a hybrid between a local search procedure and a particle swarm optimization algorithm with growing population size. The local search procedure provide...

-The social insect allegory for working out problems has become a promising area in the recent years emphasizing on stochastic construction practice building the key probabilistically. The approach focuses on direct or indirect communications among uncomplicated agents. Swarm Intelligence is the collective behavior of decentralized, self-organized system whereby the joint behavior of agent inte...

In this demo, we show the emergence of Swarm Intelligence in physical robots. We transferred an optimization algorithm which is based on bee-foraging behavior to a robotic swarm with the advantage that this algorithm, and so the actual robots, do not require input of environmental parameters (e.g., pheromones).

This paper presents a new approach to solve Fractional Programming Problems (FPPs) based on two different Swarm Intelligence (SI) algorithms. The two algorithms are: Particle Swarm Optimization, and Firefly Algorithm. The two algorithms are tested using several FPP benchmark examples and two selected industrial applications. The test aims to prove the capability of the SI algorithms to s...