A Parallel Interval Computation Model with Alternative Message Passing
In this paper, we propose a decentralized parallel computation model for global optimization using interval analysis. The model is adaptive to any number of processors and there is no need to design an initial decomposition scheme to feed each processor at the beginning. The work load is distributed evenly among all processors by alternative message passing. Numerical experiments indicate that the model works well and is stable with different number of parallel processors, distributes the load evenly among the processors, and provides an impressive speedup, especially when the problem is time-consuming to solve.
global optimization interval analysis parallel processing computation model branch-and-bound
Yong Wu Arun Kumar Peng Shi
Institute for Logistics and Supply Chain Management,Victoria University,Melbourne Australia School of Aerospace,Mechanical & Manufacturing Engineering,RMIT University,Melbourne Australia
国际会议
南京
英文
459-462
2010-08-26（万方平台首次上网日期，不代表论文的发表时间）