large-scale network plan optimization using improved particle swarm optimization algorithm

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ID: 247217
2017
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Abstract
No relevant reports have been reported on the optimization of a large-scale network plan with more than 200 works due to the complexity of the problem and the huge amount of computation. In this paper, an improved particle swarm optimization algorithm via optimization of initial particle swarm (OIPSO) is first explained by the stochastic processes theory. Then two optimization examples are solved using this method which are the optimization of resource-leveling with fixed duration and the optimization of resources constraints with shortest project duration in a large network plan with 223 works. Through these two examples, under the same number of iterations, it is proven that the improved algorithm (OIPSO) can accelerate the optimization speed and improve the optimization effect of particle swarm optimization (PSO).
Reference Key
zhang2017mathematicallarge-scale Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors ;Houxian Zhang;Zhaolan Yang
Journal journal of power sources
Year 2017
DOI
10.1155/2017/3271969
URL
http://dx.doi.org/10.1155/2017/3271969
Keywords
civil engineering (general)mathematics engineering (general)

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