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In cloud computing environment, there is a large quantity of submitted tasks by users. How to schedule these massive tasks efficiently and reasonably becomes a serious challenge. This paper proposes a Chaotic Particle Swarm Optimization algorithm (CPSO) to overcome the problems of Standard Particle Swarm algorithm such as premature convergence and low accuracy. Firstly, in initial process, chaotic...
To avoid falling into local optimum solution and improve global optimum efficiency and accuracy of particle swarm optimization, a novel particle swarm optimization model with centroid of population is proposed, which can enhance inter-particle cooperation and information sharing capabilities effectively, then the guidelines of parameter selection are obtained in the case of convergence of the new...
We summarized recent research aimed at expanding the context of facility location decisions to incorporate additional features of a supply chain including variable construction cost, inventory management, transportation cost, etc. Authors expended location model of risk pooling with variable construction cost (LMRPVCC) to construct location model of risking pool with variable construction cost with...
According to the intelligent behavior of social population, two novel particle swarm algorithm optimization models are proposed by enhancing collaboration and information sharing capabilities of individuals. Benchmark function simulation results show the new algorithms, with both a better stability and a steady convergence, not only enhance the local searching efficiency and global searching performance...
The back-analysis of mechanics parameters needs iterative forward calculating, resulting in low efficiency; meanwhile the Particle Swarm Optimization (PSO) algorithm and other optimization algorithms are exposed to local optimum possibilities. In this paper, DEPSO-ParallelFEM, a system integrated of an algorithm of hybrid particle swarm with Differential Evolution (DE) operator, termed DEPSO, and...
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