A MODIFIED BINARY PARTICLE SWARM OPTIMIZATION ALGORITHM FOR PERMUTATION FLOW SHOP PROBLEM

摘要：

In this paper, we proposed a modified version of binary particle swarm optimization algorithm (MBPSO) to solve combinatorial optimization problems.All particles are initialized as random binary vectors, and the Smallest Position Value (SPV) rule is used to construct a mapping from binary space to the permutation space.We also propose new formula to update the particles velocities and positions.The algorithm is then applied to the permutation flow shop problem (PFSP).To avoid the stagnation, local search and perturbation are employed to improve the performance.Performance of the proposed algorithm is evaluated using the benchmarks of flow shop scheduling problems given by Taillard 1.Experimental results show that the algorithm with local search and perturbation is more effective.

关键词： Binary particle swarm optimization Flow shop problem Local search Perturbation SPV rule

作者: LEI YUAN ZHEN-DONG ZHAO

作者单位: School of Communication and Information Engineering, Nanjing University of Posts and Telecommunicati Institute of information and networking, Nanjing University of Posts and Telecommunications, Nanjing

会议类型: 国际会议

会议名称: 2007 International Conference on Machine Learning and Cybernetics(IEEE第六届机器学习与控制论国际会议)

会议地点: 香港

会议语种:英文

页码: 902-907

在线出版日期: 2007-08-19（万方平台首次上网日期，不代表论文的发表时间）