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Mathematical Problems in Engineering
Volume 2017, Article ID 3271969, 15 pages
https://doi.org/10.1155/2017/3271969
Research Article

Large-Scale Network Plan Optimization Using Improved Particle Swarm Optimization Algorithm

1School of Architecture and Civil Engineering, Nanjing Institute of Technology, Nanjing 211167, China
2Industrial Center, Nanjing Institute of Technology, Nanjing 211167, China

Correspondence should be addressed to Houxian Zhang; moc.anis@gnahznaixuoh

Received 21 October 2016; Revised 12 January 2017; Accepted 29 January 2017; Published 27 February 2017

Academic Editor: Shuming Wang

Copyright © 2017 Houxian Zhang and Zhaolan Yang. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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).