Balancing assembly lines, a family of optimization problems commonly known as Assembly Line Balancing Problem, is notoriously NP-Hard. They comprise a set of problems of enormous practical interest to manufacturing industry due to the relevant frequency of this type of production paradigm. For this reason, many researchers on Computational Intelligence and Industrial Engineering have been conce...

The technique for point pattern matching (PPM) is essential to many image analysis and computer vision tasks. Given two point patterns, the PPM technique finds an optimal transformation for one point pattern such that a distance measure from the transformed point pattern to the other is minimized. This paper presents a new PPM algorithm based on particle swarm optimization (PSO). The set of tra...

This paper builds a soft sensor model based on a PSO-BP neural network for titanium billet heating furnace-temperature. An improved particle swarm optimization algorithm is proposed. This algorithm is used to optimize the initial weights of the neural network, which can overcome the disadvantages of the random initial weights of the conventional BP neural networks. The proposed algorithm is bas...

For many practical optimization problems, the evaluation of a solution is subject to noise, and optimization heuristics capable of handling such noise are needed. In this paper, we examine the influence of noise on particle swarm optimization and demonstrate that the resulting stagnation can not be removed by parameter optimization alone, but requires a reduction of noise through averaging over...

Due to the fact that Swarm Systems algorithms have been determined to be efficient in solving discrete optimization problems with proven applicability into practical world, the computer scientists are continuously and increasingly discovering swarm-inspired algorithms or improving existing ones. The scope of this paper is to present such an improvement brought to the Elitist Ant System (EAS) al...

Wireless sensor networks (WSNs) have attracted a great deal of research due to their wide-range of potential applications. Sensor deployment and coverage problems are their important issues. This article briefly introduces the principle of swarm intelligence (SI). A novel SI algorithm based on information sharing of Particle Swarm Optimization (PSO) and diversity maintenance mechanism of Artifi...

This paper presents a new approach to economic dispatch (ED) problems with nonsmooth cost functions using a particle swarm optimization (PSO) technique. The practical ED problems have nonsmooth cost functions with equality and inequality constraints, which makes the problem of finding the global optimum difficult when using any mathematical approaches. In this paper, a modified PSO (MPSO) mecha...

A mathematical model for ATC based on optimal power flow was built under the static security constraints, where the maximum of all load nodes in receiving area was considered as aim function. In view of the defects of slow convergence and low accuracy in ATC optimization algorithms, a chaos cloud particle swarm optimization algorithm based on golden section criteria (CCGPSO) was proposed. This ...

Hierarchical clustering algorithm of cluster analysis method can detect data in different granularity levels, and the clustering process is suitable for most of practical problems, but complexity of the merger and split conditions limits its application. This paper proposed a new hierarchical clustering algorithm basis on dynamic fuzzy granular computing combining with the particle swarm optimi...

This chapter presents a classification of different schemes for the cooperation of multiple UAVs taking into account the coupling between the vehicles and the type of cooperation. Then, the research and development activities in load transportation, formation control, swarm approaches and intentional cooperation architectures are revised. The chapter also considers UAVs networked with other ele...