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An optimized IS-APCPSO algorithm for large scale complex traffic network

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成果类型:
期刊论文
作者:
Huang, Ke;Zhang, Hao Lan*;Yang, Gelan
通讯作者:
Zhang, Hao Lan
作者机构:
[Zhang, Hao Lan; Huang, Ke] Zhejiang Univ, SCDM Ctr, Ningbo Inst Technol, Ningbo, Zhejiang, Peoples R China.
[Yang, Gelan] Hunan City Univ, Sch Informat Sci & Engn, Heshan, Peoples R China.
通讯机构:
[Zhang, Hao Lan] Z
Zhejiang Univ, SCDM Ctr, Ningbo Inst Technol, Ningbo, Zhejiang, Peoples R China.
语种:
英文
关键词:
Optimization;IS-APCPSO algorithm;Traffic network;Immune selection
期刊:
Cluster Computing
ISSN:
1386-7857
年:
2019
卷:
22
期:
2
页码:
3271-3284
基金类别:
This research was supported by Zhejiang Provincial Natural Science Foundation of China under Grant No. LQ17G030007. This research was supported by Ningbo Soft Science Project under Grant No. 2017A10070, Ningbo Innovation Team (Grant No. 2016C11024), Zhejiang Provincial Natural Science Foundation of China under Grant No. LY14G010004, and National Natural Science Foundation of China under Grant No. 61272480.
机构署名:
本校为其他机构
院系归属:
信息与电子工程学院
摘要:
Chaotic particle swarm optimization algorithm is improved by incorporating antibody concentration, adaptive propagation, optimization mechanism of the multi-population evolution strategy, elite particles chaotic traversal mechanism and constraint processing mechanism. In this paper, an improved adaptive propagation chaotic particle swarm optimization algorithm based on immune selection (IS-APCPSO algorithm for short) is proposed. The performance of several algorithms has been compared by multimodal function, functions with high dimensional and complex constraints, bi-level programming function...

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