This paper presents a new optimization algorithm – MCPSO, multi-swarm cooperative particle swarm optimizer, inspired by the phenomenon of symbiosis in natural ecosystems. MCPSO is based on a master–slave model, in which a population consists of one master swarm and several slave swarms. The slave swarms execute a single PSO or its variants independently to maintain the diversity of particles, w...

Bare bones PSO is a simple swarm optimization approach that uses a probability distribution like Gaussian distribution in the position update rules. However, due to its nature, Bare bones PSO is highly prone to premature convergence and stagnation. The characteristics of the probability distribution functions used in the update rule have a tense impact on the performance of the bare bones PSO. ...

Swarm-based systems have emerged as an attractive paradigm for implementing distributed autonomous systems for various applications in commercial, military and business domains. One of the major operations in a swarm-based system is to ensure that the individual swarm units process the tasks in the environment in an efficient manner. This can be achieved using a suitable task selection mechanis...

Multi-objective particle swarm optimization (MOPSO) is an optimization technique inspired by bird flocking, which has been steadily gaining attention from the research community because of its high convergence speed. On the other hand, in the face of increasing complexity and dimensionality of today’s application coupled with its tendency of premature convergence due to the high convergence spe...

A mathematical model for dynamic fleet planning with multi routes and multi ship, which took the maximum total operation profits as its objective function, was built up according to the characteristics of the shipping company. The model had the following characteristics: Firstly in the model, the long-term fleet planning and short-term scheduling were combined. Secondly, the economic and techno...

Original scientific paper Economic Load Dispatch problem has been previously solved successfully with swarm techniques. However, power systems with complex behaviours still await a robust algorithm to be developed for their optimization more precisely. Economic Dispatch problem with constraints such as generator limits, total power demand, ramp rate limits and prohibited operating zones, makes ...

Swarm stability is concerned for descriptor compartmental networks with linear time-invariant protocol. Compartmental network is a specific type of dynamical multi-agent system. Necessary and sufficient conditions for both consensus and critical swarm stability are presented, which require a joint matching between the interactive dynamics of nearest neighboring vertices and the Laplacian spectr...

Aiming at the task allocation in multi-target tracking of wireless sensor networks, the discrete particle swarm optimization based on nearest-neighbor is presented to reduce the communication energy consumption between nodes. First, task allocation is initialized with nearest neighbor algorithm. Then the fitness function is compared through change task allocation matrix to achieve task allocati...