An efficient flow-shop scheduling algorithm based on a hybrid particle swarm optimization model

Authors:
I-Hong Kuo;Shi-Jinn Horng;Tzong-Wann Kao;Tsung-Lieh Lin;Pingzhi Fan
Affiliations:
Department of Electrical Engineering, National Taiwan University of Science and Technology, Taipei;Southwest Jiaotong Univ., Chengdu and Dept. of Elect. Eng., Natl. Taiwan Univ. of Sci. and Techn., Taipei and Dept. of Comp. Sci. and Inf. Eng., Natl. Taiwan Univ. of Sci. and Techn., Taipei and D ...;Department of Electronic Engineering, Technology and Science Institute of Northern Taiwan, Taipei;Department of Electrical Engineering, National Taiwan University of Science and Technology, Taipei;Institute of Mobile Communications, Southwest Jiaotong University, Chengdu
Venue:
IEA/AIE'07 Proceedings of the 20th international conference on Industrial, engineering, and other applications of applied intelligent systems
Year:
2007

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Abstract

In this paper, a new hybrid particle swarm optimization model named HPSO that combines random-key (RK) encoding scheme, individual enhancement (IE) scheme, and particle swarm optimization (PSO) is presented and used to solve the flow-shop scheduling problem (FSSP). The objective of FSSP is to find an appropriate sequence of jobs in order to minimize makespan. Makespan means the maximum completion time of a sequence of jobs running on the same machines in flow-shops. By the RK encoding scheme, we can exploit the global search ability of PSO thoroughly. By the IE scheme, we can enhance the local search ability of particles. The experimental results show that the solution quality of FSSP based on the proposed HPSO is far better than those based on GA [1] and NPSO [1], respectively.