Particle swarm optimization is affected by premature convergence, no guarantee in finding optimal solution, lack of solution amongst other issues. This paper reviews many literature on PSO and proposes a Hybrid MultiSearch Sub-Swarm PSO by using multiple sub swarm PSO in combination with multi search space algorithm. The particles are divided into equal parts and deployed into the number of sub...

Swarm robotics is a relatively new field that focuses on controlling large-scale homogeneous multi-robot systems. We survey six example swarm robotics control algorithms to give a brief overview of the current state of the cutting-edge. Experimental results show that swarm robotics algorithms are scalable, fault tolerant, robust and efficient. These favorable results stem from the algorithms be...

In light of the accuracy of particle swarm optimization-particle filter (PSO-PF) inadequate for multi-robot cooperative positioning, the paper presents population density particle swarm optimization-particle filter (PDPSO-PF), which draws cooperative coevolutionary algorithm in ecology into particle swarm optimization. By taking full account of the competitive relationship between the environme...

Swarm Microrobotics aims to apply Swarm Intelligence algorithms and strategies to a large number of fabricated miniaturized autonomous or semi-autonomous agents, allowing collective, decentralized and self-organizing behaviors of the robots. The ability to establish basic information networking is fundamental in such swarm systems, where inter-robot communication is the base of emergent behavio...

This Paper represents a literature review of Swarm intelligence algorithm in the area of semi-supervised classification. There are many research papers for applying swarm intelligence algorithms in the area of machine learning. Some algorithms of SI are applied in the area of ML either solely or hybrid with other ML algorithms. SI algorithms are also used for tuning parameters of ML algorithm, ...

During reproductive swarming, honey bee scouts perform two very important functions. Firstly, they find new nesting locations and return to the swarm cluster to communicate their discoveries. Secondly, once the swarm is ready to depart, informed scout bees act as guides, leading the swarm to its final destination. We have previously hypothesised that the two processes, selecting a new nest site...

The objective of this thesis is to investigate how to improve Particle Swarm Optimization by hybridization of stochastic search heuristics and by a Self-Organized Criticality extension. The thesis will describe two hybrid models extending Particle Swarm Optimization with two aspects from Evolutionary Algorithms, recombination via breeding and gene flow restriction via subpopulations. A further ...

The research field of swarm intelligence contains various algorithms inspired from the particular survival skills of the creatures in Mother Nature. Many researchers utilize these methods to solve problems in engineering and financial fields. In this review, the concept of four swarm intelligence methods, including Bat Algorithm (BA), Evolved Bat Algorithm (EBA), Cat Swarm Optimization (CSO), a...

The CoCoRo system will consist of several subsystems: A 'floating base station', which feeds global information (e.g., GPS) into the system, a self-aware 'ground swarm' that performs the focal task and a 'relay swarm' that bridges the communication between the these two agents. Both, the ground swarm and the relay swarm consist of AUVs able to perform 3D underwater swimming, with many on-board ...

In this paper we present and discuss the results of experimentally comparing the performance of several variants of the standard swarm particle optimiser and a new approach to swarm based optimisation. The new algorithm, which we call predator prey optimiser, combines the ideas of particle swarm optimisation with a predator prey inspired strategy, which is used to maintain diversity in the swar...