Hybrid particle swarm optimization with chaotic search for solving integer and mixed integer programming problems

TAN Yue(谭跃)^{1, 2}, TAN Guan-zheng(谭冠政)¹, DENG Shu-guang(邓曙光)²

(1. School of Information Science and Engineering, Central South University, Changsha 410083, China;
2. School of Communication and Electronic Engineering, Hunan City University, Yiyang 413000, China)

Abstract:A novel chaotic search method is proposed, and a hybrid algorithm combining particle swarm optimization (PSO) with this new method, called CLSPSO, is put forward to solve 14 integer and mixed integer programming problems. The performances of CLSPSO are compared with those of other five hybrid algorithms combining PSO with chaotic search methods. Experimental results indicate that in terms of robustness and final convergence speed, CLSPSO is better than other five algorithms in solving many of these problems. Furthermore, CLSPSO exhibits good performance in solving two high-dimensional problems, and it finds better solutions than the known ones. A performance index (PI) is introduced to fairly compare the above six algorithms, and the obtained values of (PI) in three cases demonstrate that CLSPSO is superior to all the other five algorithms under the same conditions.

Key words:particle swarm optimization; chaotic search; integer programming problem; mixed integer programming problem