Heterogeneous Particle Swarm Optimizer and its Application in Aircraft Manufacturing Logistics

Yulian Cao; Mengchu Zhou; Wenfeng Li; Gabriel Lodewijks

doi:10.1109/ICNSC48988.2020.9238107

Heterogeneous Particle Swarm Optimizer and its Application in Aircraft Manufacturing Logistics

Yulian Cao, Mengchu Zhou, Wenfeng Li, Gabriel Lodewijks

Electrical and Computer Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

Particle swarm optimization (PSO) attracts much attention due to its ability in solving complex practical engineering problems effectively. To further improve its performance, a heterogeneous particle swarm optimizer (HPSO) is proposed in this work. Five widely used benchmark functions are selected to test its efficiency. Furthermore, five state-of-the-art improved PSO variants are selected for a comparisons purpose. The results demonstrate that HPSO is better than the other five algorithms. A logistics problem in aircraft manufacturing is then studied and solved. The results show HPSO's superiority over its tested PSO variants.

Original language	English (US)
Title of host publication	2020 IEEE International Conference on Networking, Sensing and Control, ICNSC 2020
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9781728168531
DOIs	https://doi.org/10.1109/ICNSC48988.2020.9238107
State	Published - Oct 30 2020
Event	2020 IEEE International Conference on Networking, Sensing and Control, ICNSC 2020 - Nanjing, China Duration: Oct 30 2020 → Nov 2 2020

Publication series

Name	2020 IEEE International Conference on Networking, Sensing and Control, ICNSC 2020

Conference

Conference	2020 IEEE International Conference on Networking, Sensing and Control, ICNSC 2020
Country	China
City	Nanjing
Period	10/30/20 → 11/2/20

All Science Journal Classification (ASJC) codes

Artificial Intelligence
Computer Networks and Communications
Statistics, Probability and Uncertainty
Control and Optimization
Sensory Systems

Keywords

aircraft manufacturing logistics
evolutionary computation
facility location
particle swarm optimizer (PSO)

Access to Document

10.1109/ICNSC48988.2020.9238107

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Cite this

Cao, Y., Zhou, M., Li, W., & Lodewijks, G. (2020). Heterogeneous Particle Swarm Optimizer and its Application in Aircraft Manufacturing Logistics. In 2020 IEEE International Conference on Networking, Sensing and Control, ICNSC 2020 [9238107] (2020 IEEE International Conference on Networking, Sensing and Control, ICNSC 2020). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICNSC48988.2020.9238107

Cao, Yulian ; Zhou, Mengchu ; Li, Wenfeng ; Lodewijks, Gabriel. / Heterogeneous Particle Swarm Optimizer and its Application in Aircraft Manufacturing Logistics. 2020 IEEE International Conference on Networking, Sensing and Control, ICNSC 2020. Institute of Electrical and Electronics Engineers Inc., 2020. (2020 IEEE International Conference on Networking, Sensing and Control, ICNSC 2020).

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abstract = "Particle swarm optimization (PSO) attracts much attention due to its ability in solving complex practical engineering problems effectively. To further improve its performance, a heterogeneous particle swarm optimizer (HPSO) is proposed in this work. Five widely used benchmark functions are selected to test its efficiency. Furthermore, five state-of-the-art improved PSO variants are selected for a comparisons purpose. The results demonstrate that HPSO is better than the other five algorithms. A logistics problem in aircraft manufacturing is then studied and solved. The results show HPSO's superiority over its tested PSO variants.",

keywords = "aircraft manufacturing logistics, evolutionary computation, facility location, particle swarm optimizer (PSO)",

author = "Yulian Cao and Mengchu Zhou and Wenfeng Li and Gabriel Lodewijks",

note = "Funding Information: This work was partly supported by the NSFC under Grant No. 61571336. Publisher Copyright: {\textcopyright} 2020 IEEE. Copyright: Copyright 2020 Elsevier B.V., All rights reserved.; 2020 IEEE International Conference on Networking, Sensing and Control, ICNSC 2020 ; Conference date: 30-10-2020 Through 02-11-2020",

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Cao, Y, Zhou, M, Li, W & Lodewijks, G 2020, Heterogeneous Particle Swarm Optimizer and its Application in Aircraft Manufacturing Logistics. in 2020 IEEE International Conference on Networking, Sensing and Control, ICNSC 2020., 9238107, 2020 IEEE International Conference on Networking, Sensing and Control, ICNSC 2020, Institute of Electrical and Electronics Engineers Inc., 2020 IEEE International Conference on Networking, Sensing and Control, ICNSC 2020, Nanjing, China, 10/30/20. https://doi.org/10.1109/ICNSC48988.2020.9238107

Heterogeneous Particle Swarm Optimizer and its Application in Aircraft Manufacturing Logistics. / Cao, Yulian; Zhou, Mengchu; Li, Wenfeng; Lodewijks, Gabriel.

2020 IEEE International Conference on Networking, Sensing and Control, ICNSC 2020. Institute of Electrical and Electronics Engineers Inc., 2020. 9238107 (2020 IEEE International Conference on Networking, Sensing and Control, ICNSC 2020).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

TY - GEN

T1 - Heterogeneous Particle Swarm Optimizer and its Application in Aircraft Manufacturing Logistics

AU - Cao, Yulian

AU - Zhou, Mengchu

AU - Li, Wenfeng

AU - Lodewijks, Gabriel

PY - 2020/10/30

Y1 - 2020/10/30

N2 - Particle swarm optimization (PSO) attracts much attention due to its ability in solving complex practical engineering problems effectively. To further improve its performance, a heterogeneous particle swarm optimizer (HPSO) is proposed in this work. Five widely used benchmark functions are selected to test its efficiency. Furthermore, five state-of-the-art improved PSO variants are selected for a comparisons purpose. The results demonstrate that HPSO is better than the other five algorithms. A logistics problem in aircraft manufacturing is then studied and solved. The results show HPSO's superiority over its tested PSO variants.

AB - Particle swarm optimization (PSO) attracts much attention due to its ability in solving complex practical engineering problems effectively. To further improve its performance, a heterogeneous particle swarm optimizer (HPSO) is proposed in this work. Five widely used benchmark functions are selected to test its efficiency. Furthermore, five state-of-the-art improved PSO variants are selected for a comparisons purpose. The results demonstrate that HPSO is better than the other five algorithms. A logistics problem in aircraft manufacturing is then studied and solved. The results show HPSO's superiority over its tested PSO variants.

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KW - evolutionary computation

KW - facility location

KW - particle swarm optimizer (PSO)

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BT - 2020 IEEE International Conference on Networking, Sensing and Control, ICNSC 2020

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Cao Y, Zhou M, Li W, Lodewijks G. Heterogeneous Particle Swarm Optimizer and its Application in Aircraft Manufacturing Logistics. In 2020 IEEE International Conference on Networking, Sensing and Control, ICNSC 2020. Institute of Electrical and Electronics Engineers Inc. 2020. 9238107. (2020 IEEE International Conference on Networking, Sensing and Control, ICNSC 2020). https://doi.org/10.1109/ICNSC48988.2020.9238107