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| Discrete Particle Swarm Optimization Algorithm for Independent Task Assignment Problem |
| ZHONG YiWen1,2, YANG JianGang2 |
1.College of Computer and Information, Fujian Agriculture and Forestry University, Fuzhou 350002
2.College of Computer Science and Technology, Zhejiang University, Hangzhou 310027 |
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Abstract A discrete particle swarm optimization algorithm is designed to tackle the independent task assignment problem in heterogeneous computing systems. Based on the characteristics of discrete variable, particle’s position, velocity and their operation rules are redefined in this paper. In order to restrain premature stagnation, individual diversity of particle and microdiversity of particle swarm are defined. A repulsion operator is designed to keep the diversity of particle swarm, and a learning operator is defined to improve intensification ability of the algorithm. The proposed algorithm gets good balance between exploration and exploitation using those operators. The simulation results show the proposed algorithm has good performance comparing with a hybrid genetic algorithm and a list scheduling, both typical from the literature.
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Received: 14 April 2005
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2006, Vol. 19 
