Sigmoid surface controller has been proved to be effective in motion control of autonomous underwater vehicles, but it is hard to adjust its control parameters. Improved particle swarm optimization of sigmoid surface controller was proposed in this paper, which solves the problems that particle swarm optimization may be trapped in local optimum and fails to converge to global optimum. Moreover,...

We consider a swarm-intelligent inspection system concerned with the inspection of blades in a jet turbine. The system is based on a swarm of autonomous, miniature robots, using only on-board, local sensors. We capture the dynamics of the system at a higher abstraction level using non-spatial, probabilistic, discrete-time macroscopic models, which we use in an optimal control framework to find ...

In this paper, the idea of a new artificial intelligence based optimization algorithm, which is inspired from the nature of vortex, has been provided briefly. As also a bio-inspired computation algorithm, the idea is generally focused on a typical vortex flow / behavior in nature and inspires from some dynamics that are occurred in the sense of vortex nature. Briefly, the algorithm is also a sw...

In this paper we attempt to integrate production scheduling and distribution routing problems to minimize the total cost of the supply chain under uncertain environments. The particle swarm optimization method is used to select the location of the distribution center, combining it with the tabu search algorithm to solve vehicle distribution route problem. Especially, the location of each partic...

Swarm robotics is focused on creating intelligent systems from large number of simple robots. The majority of nowadays robots are bound to operations within mono-modal locomotion (i.e. land, air or water). However, some animals have the capacity to alter their locomotion modalities to suit various terrains, operating at high levels of competence in a range of substrates. One of the most signifi...

This study proposes a novel bacterial foraging swarm-based intelligent algorithm called the bacterial foraging particle swarm optimization (BFPSO) algorithm to design vector quantization (VQ)-based fuzzy-image compression systems. It improves compressed image quality when processing many image patterns. The BFPSO algorithm is an efficient evolutionary learning algorithm that manages complex glo...

Underwater exploration is important for mapping out the oceans, environmental monitoring, and search and rescue, yet water represents one of the most challenging of operational environments. The CoCoRo project proposes to address these challenges using cognitive swarm intelligent systems. We present here CoCoRoSim, an underwater swarm robotics simulation used in designing underwater swarm robot...

Particle swarm optimization (PSO) is becoming one of the most important swarm intelligent paradigms for solving global optimization problems. Although some progress has been made to improve PSO algorithms over the last two decades, additional work is still needed to balance parameters to achieve better numerical properties of accuracy, efficiency, and stability. In the optimal PSO algorithm, th...

This paper provides evidence that Evolutionary Particle Swarm Algorithms outperform Genetic Algorithms in deriving optimal strategic decisions for an Energy Retailer, in the framework of a complex simulation of a multiple energy market, based on an Intelligent Agent FIPA-compliant open source

algorithms are worthy of considering and efficiently to be utilized in the network topological deployment and keeping the network integrity, (2) the Partial Swarm Optimization is much algorithmically easier and reliable, (3) Intelligent computation is a kind of optimal methodology to improve the network integrity.