Multidisciplinary Collaborative Optimization for Product Design Based on Dual-Loop Wolf Pack Algorithm

  • Xuerui Zhao
  • , Zian Zhao
  • , Hong Zhou*
  • *Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Complex product design generally involves multiple subdisciplines or subsystems. In this study, taking the two-stage planetary gear transmission system as an example, a multi-objective optimization model for multidisciplinary design is established and solved by collaborative optimization method. The goal of the optimization is to simultaneously minimize volume and maximize efficiency. In the model, the sequential quadratic programming (SQP) method is used for individual disciplinary optimization, and an improved wolf pack algorithm is developed as the optimizer at system level for the CO method. It is shown that the proposed method can realize the requirement of miniaturization of the part while ensuring the transmission efficiency almost undamaged, and obtains accurate and efficient optimization results.

Original languageEnglish
Title of host publicationInternational Conference on Intelligent Manufacturing and Industrial Automation, CIMIA 2022
EditorsParames Chutima, Ayush Dogra
PublisherSPIE
ISBN (Electronic)9781510655966
DOIs
StatePublished - 2022
Event2022 International Conference on Intelligent Manufacturing and Industrial Automation, CIMIA 2022 - Kunming, China
Duration: 25 Mar 202227 Mar 2022

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
Volume12289
ISSN (Print)0277-786X
ISSN (Electronic)1996-756X

Conference

Conference2022 International Conference on Intelligent Manufacturing and Industrial Automation, CIMIA 2022
Country/TerritoryChina
CityKunming
Period25/03/2227/03/22

Keywords

  • Dual-Loop Wolf Pack Algorithm
  • Multidisciplinary Collaborative Optimization
  • Product Design

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