With the rapid development of social economy, all circles places higher demands on electricity industry. As a fundamental industry supporting salvation national society, and human life, will face significant improvement restructuring network as an important part power system should also be optimised. This paper first introduces history swarm intelligence algorithm related research work at home ...

Based on the combination of the particle swarm algorithm and multiplier penalty function method for the constraint conditions, this paper proposes an improved hybrid particle swarm optimization algorithm which is used to solve nonlinear constraint optimization problems. The algorithm converts nonlinear constraint function into no-constraints nonlinear problems by constructing the multiplier pen...

Abstract: One of the equipment that can help improve distribution system status today and reduce the cost of fault time is remote control switches (RCS). Finding the optimal location and number of these switches in the distribution system can be modeled with various objective functions as a nonlinear optimization problem to improve system reliability and cost. In this article, a particle swarm ...

With the target of achieving dense storage of packed medicine of rapid dispensing system in automated pharmacy, an improved adaptive chaotic particle swarm optimization (IACPSO) algorithm was proposed to solve the storage planning problem. According to the proposed IACPSO algorithm, the diversity of the particle swarm was enhanced by using the ergodicity of the chaos motion to initialize the sw...

This paper assumes each user has more than one queue, derives a new packet-dependant proportional fairness power allocation pattern based on the sum of weight capacity and the packet’s priority in users’ queues, and proposes 4 new cross-layer packet-dependant OFDM scheduling schemes based on proportional fairness for heterogeneous classes of traffic. Scenario 1, scenario 2 and scenario 3 lead r...

Clustering is a method which divides data objects into groups based on the information found in data that describes the objects and relationships among them. There are a variety of algorithms have been developed in recent years for solving problems of data clustering. Data clustering algorithms can be either hierarchical or partitioned. Most promising among them are K-means algorithm which is p...