To adapt the changing of market need, logistics providers in efforts to reduce costs and improve customer service levels to meet the customer satisfaction as individual demands. The actual distribution process, delivery vehicles will encounter various often uncertain external factors, resulting in delivery...

A new approach is presented to solve nonlinear constrained programming problems (NLCPs) by using particle swarm algorithm(PSO). It neither uses any penalty functions, nor distinguish the feasible solutions and the infeasible solutions including swarm. The new technique treats the NLCPs as a bi-objective...

In electricity industry, accurate load forecasting plays a key role in assuring the stability of power network and society. By far, there are many methods and models proposed to enhance the accuracy of forecasting results. On the basis of analyzing the performance of particle swarm algorithm (PSA) and...

In our previous work, a new PSO algorithm called ?-PSO based on phase angle was put forward, which has better optimization performance than standard PSO algorithm when dealing with some simple benchmark functions. But this algorithm may easily stick in the local minima when handling some complex or multi-mode...

This paper proposes a shuffled sub-swarms particle optimizer algorithm (SSPSO) to enhance the diversity of particles in the swarm to improve the performance of PSO. SSPSO is tested with a series of benchmark functions and compared with other version PSO algorithms. Experimental results show that SSPSO...

It is very difficult to solve the large-scaled in the semiconductor device simulation, sparse and ill-conditioned matrix equation exactly and quickly. So the particle swarm optimization algorithm(PSO) based on the swarm intelligent technology is presented to get the global optimal solution of the matrix...

In emotion recognition, many irrelevant and redundant features will affect recognition results, so feature selection is necessary. Aimed at emotion physiological signal feature selection, this paper proposed with improved discrete binary particle swarm optimization(BPSO) to increase the correct classification...

The ant system is a metaheuristic developed for the solution of hard combinatorial optimization problems. In this paper, through an analysis of the constructive procedure of the solution in the Ant Colony System (ACS), a modified algorithm for solving Vehicle Routing Problem (VRP), based on the ACS Hybridized...

After an introduction of the principle of particle swarm optimization (PSO) algorithm based on swarm intelligence, and of the modified version of the PSO algorithm, a neural network system for gearbox fault diagnosis has been established. After being trained by PSO algorithm, the neural network system...

Optimization of multi-flight refueling service scheduling is very important for the recovery efficiency of flight delays. After analyzing the constraints and objective of multi-flight refueling service scheduling problem, a model is put forward. A novel particle swarm optimization is designed to solve...

Based on the metaphor of specialization and cooperation in hierarchical social organization, a new particle swarm optimization (PSO) algorithm, hierarchical subpopulation PSO (HS-PSO), was proposed. In HS-PSO, the entire population is divided into several subpopulations which are arranged in a hierarchy....