Earticle

초록

영어

With the development of computer technology, more and more intelligent algorithms in the solution of different problems in many aspects of society are extensively used. Calculation of the minimum values of the function optimization and finding the optimal solution of combinatorial optimization problems in certain space are the two typical problems. In the fields of science and engineering, many optimization problems are constrained with different conditions. Due to the existence of constraints, the optimization problems are more difficult than the unconstrained optimization problem. Therefore, research on how to make the objective function find the optimal solution in the feasible region is of great significance As an important intelligent algorithm, particle swarm optimization (PSO) is widely used in the calculation of the optimal solution of the constraint problems. But due to the disadvantages of the PSO, its search efficiency is quite low when the particle is close to the optimal value. On the other side, it is easy to search the local optimal solution but difficult to get the global optimal solution. So, it is necessary to modify the algorithm to improve the performance. In the paper, we modify the algorithm and propose a modified algorithm (M-PSO). With the simulation, the results show the validity of the algorithm.

목차

Abstract
 1. Introduction
 2. PSO
  2.1. Standard PSO Algorithm
  2.2. Discrete Particle Swarm Optimization Algorithm (DPSO)
  2.3. Flow Chart of PSO
 3. Modified PSO
  3.1. Trust Region combined Inertia Weight
  3.2. Processing of Constraints
  3.3. Flow Chart of Modified Algorithm
 4. Application
 5. Conclusion
 References

키워드

저자

• Kang Lv [ Henan Institute of Education, Zhengzhou, Henan, China ]
• Yuanyuan Ma [ Henan Normal University, Xinxiang, Henan, China ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Multimedia and Ubiquitous Engineering

• 간기

  월간

• pISSN

  1975-0080

• 수록기간

  2008~2016

• 등재여부

  SCOPUS

• 십진분류

  KDC 505 DDC 605