Design of College Discrete Mathematics Based on Particle Swarm Optimization

DOI

10.2991/icmmcce-15.2015.232How to use a DOI?

Keywords

Discrete mathematics, Particle swarm optimization, Exchange of information, Mutation operator

Abstract

Aiming at exploration and development capacity, it is usually hard to achieve effective utilization and balance by using just one algorithm, which will influence the solving accuracy and efficiency of the algorithm accordingly. This thesis applies particle swarm optimization (PSO) to discrete multi-objective mathematical optimization, and proposes a discrete multi-objective optimization algorithm based on PSO. This algorithm adopts binary mechanism to achieve the position vector of the particles. Meanwhile, it builds a non-dominated solution set to storage the researched non-dominated solution, so as to increase the diversity of non-dominated solutions. The introductions of genetic algorithm crossover, mutation operator replacing particle velocity and location updating have reduced the computational complexity. In the thesis, it sets up mathematical models for these two problems respectively, and the experimental results show that the algorithm is effective.

Copyright

© 2015, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Jiedong Chen
PY  - 2015/12
DA  - 2015/12
TI  - Design of College Discrete Mathematics Based on Particle Swarm Optimization
BT  - Proceedings of the 4th International Conference on Mechatronics, Materials, Chemistry and Computer Engineering 2015
PB  - Atlantis Press
SN  - 2352-538X
UR  - https://doi.org/10.2991/icmmcce-15.2015.232
DO  - 10.2991/icmmcce-15.2015.232
ID  - Chen2015/12
ER  -