A hybrid particle swarm with differential evolution operator, termed DEPSO, which provide the bell-shaped mutations with consensus on the population diversity along with the evolution, while keeps the selforganized particle swarm dynamics , is proposed. Then it is applied to a set of benchmark functions, and the experimental results illustrate its efficiency.

Article history: Available online 1 June 2010

AbsfracfThis paper introduces a particle swarm optimization-based method for solving a multi-objective generator maintenance scheduling problem with many constraints. It is shown that particle swarm optimizationbased approach is effective in obtaining feasible schedules in a reasonable time. Actual data from a practical power system was used in this study and results were compared against those...

Currently, swarm robotics is one of the most promising technologies in computer science. As technologies become smarter, the potential for swarm robotics improve and the coordination of multi robot system finds applications in various fields. This paper adds new perspective to autonomous cars by proposing to incorporate swarm robotics into it. This paper summarizes various algorithms used in sw...

This paper presents a hybrid particle swarm algorithm for solving the multiobjective reactive power dispatch problem. Modal analysis of the system is used for static voltage stability assessment. Loss minimization and maximization of voltage stability margin are taken as the objectives. Generator terminal voltages, reactive power generation of the capacitor banks and tap changing transformer se...

Nature offers us many interesting and surprising examples in which the behaviour of a group of organisms seems to have some fundamentally distinct characteristics, not shared by the individuals in that group. Different species of birds flock together, and species of fish form schools, in groups that vary in size from a handful to many millions. Meanwhile it is wellknown thatmost species of ants...

Systems of distributed artificial intelligence can be powerful tools in a wide variety of practical applications. Its most surprising characteristic, the emergent behavior, is also the most answerable for the difficulty in projecting these systems. This work proposes a tool capable to beget individual strategies for the elements of a multi-agent system and thereof providing to the group means o...

Particle swarm optimization is a based-population heuristic global optimization technology and is referred to as a swarm-intelligence technique. In general, each particle is initialized randomly which increases the iteration time and makes the result unstable. In this paper an improved clustering algorithm combined with entropy-based fuzzy clustering (EFC) is presented. Firstly EFC algorithm ge...

-Particle swarm optimization (PSO) is undoubtedly one of the most widely used swarm intelligence algorithm. Generally, each particle is assigned an initial value randomly. In this paper an improved PSO clustering algorithm based on affinity propagation (APPSO) is proposed which provides new ideas and methods for cluster analysis. Firstly the proposed algorithm get initial cluster centers by aff...

Visualization of maps to explore relevant geographic areas is one of the common practices in spatial decision scenarios. However visualizing geographic distribution with multidimensional criteria becomes a nontrivial setup in the conventional point based map space. In this work we present a novel method to generalize from point data to spatial distributions, captivating on the swarm intelligenc...