Vehicle routing problem is a NP-hard problem in combination optimization problem, It is influenced by many factors, and the process is complex. However, the search space of particle swarm algorithm is limited and prone to precocious phenomenon. In this paper, we based on the original particle swarm optimization, present a new way of location update algorithm (VPSO).VPSO in the process of solvin...

Particle Swarm Optimization is a relatively new evolutionary computation technique. It is based on the social behaviour of birds flocking or fish schooling. It was designed to find optimal regions in a search space, with the biological idea of swarms in mind. In the Particle Swarm Optimization algorithm, particles which ‘fly’ around the search space have velocities associated with them. Updatin...

Optimum scheduling of hydrothermal plants generation is of great importance to electric utilities. Many evolutionary techniques such as particle swarm optimization, differential evolution have been applied to solve these problems and found to perform in a better way in comparison with conventional optimization methods. But often these methods converge to a sub-optimal solution prematurely. This...

This paper proposes a TSK-type Neuro-Fuzzy system tuned with a novel learning algorithm. The proposed algorithm used an improved version of the standard Particle Swarm Optimization algorithm, it employs several sub-swarms to explore the search space more efficiently. Each particle in a sub-swarm correct her position based on the best other positions, and the useful information is exchanged amon...

Particle swarm optimization is a popular method for solving difficult optimization problems. There have been attempts to formulate the method in formal probabilistic or stochastic terms (e.g. bare bones particle swarm) with the aim to achieve more generality and explain the practical behavior of the method. Here we present a Bayesian interpretation of the particle swarm optimization. This inter...

This paper presents a dynamic particle swarm optimization based search for optimal fusion configuration of sensors in distributed detection network in presence of a nonstationary binary symmetric channel. The wireless channel in sensor networks is a non-stationary random process, which moves the optima of the original problem, otherwise static. The optimal fusion configuration minimizes the pro...

Big data is the slightly abstract phase which describes the relationship between the data size and data processing speed in the system. The many new information technologies the big data deliver dramatic cost reduction, substantial improvements in the required time to perform the computing task or new product and service offerings. The several complicated specific and engineering problems can b...