Particle swarm methodologies for engineering design optimization

Singiresu S Rao, Kiran K. Annamdas

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

Particle swarm methodologies are presented for the solution of constrained mechanical and structural system optimization problems involving single or multiple objective functions with continuous or mixed design variables. The particle swarm optimization presented is a modified particle swarm optimization approach, with better computational efficiency and solution accuracy, is based on the use of dynamic maximum velocity function and bounce method. The constraints of the optimization problem are handled using a dynamic penalty function approach. To handle the discrete design variables, the closest discrete approach is used. Multiple objective functions are handled using a modified cooperative game theory approach. The applicability and computational efficiency of the proposed particle swarm optimization approach are demonstrated through illustrate examples involving single and multiple objectives as well as continuous and mixed design variables. The present methodology is expected to be useful for the solution of a variety of practical engineering design optimization problems.

Original languageEnglish
Title of host publicationProceedings of the ASME Design Engineering Technical Conference
Pages507-516
Number of pages10
Volume5
EditionPARTS A AND B
DOIs
StatePublished - Dec 1 2009
EventASME 2009 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, IDETC/CIE2009 - San Diego, CA, United States
Duration: Aug 30 2009Sep 2 2009

Other

OtherASME 2009 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, IDETC/CIE2009
CountryUnited States
CitySan Diego, CA
Period8/30/099/2/09

Fingerprint

Particle Swarm
Multiple Objectives
Engineering Design
Particle Swarm Optimization
Particle swarm optimization (PSO)
Optimization Problem
Computational Efficiency
Methodology
Objective function
Computational efficiency
Cooperative Game Theory
Bounce
Penalty Function
Game theory
Design
Design optimization

ASJC Scopus subject areas

  • Mechanical Engineering
  • Computer Graphics and Computer-Aided Design
  • Computer Science Applications
  • Modeling and Simulation

Cite this

Rao, S. S., & Annamdas, K. K. (2009). Particle swarm methodologies for engineering design optimization. In Proceedings of the ASME Design Engineering Technical Conference (PARTS A AND B ed., Vol. 5, pp. 507-516) https://doi.org/10.1115/DETC2009-87237

Particle swarm methodologies for engineering design optimization. / Rao, Singiresu S; Annamdas, Kiran K.

Proceedings of the ASME Design Engineering Technical Conference. Vol. 5 PARTS A AND B. ed. 2009. p. 507-516.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Rao, SS & Annamdas, KK 2009, Particle swarm methodologies for engineering design optimization. in Proceedings of the ASME Design Engineering Technical Conference. PARTS A AND B edn, vol. 5, pp. 507-516, ASME 2009 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, IDETC/CIE2009, San Diego, CA, United States, 8/30/09. https://doi.org/10.1115/DETC2009-87237
Rao SS, Annamdas KK. Particle swarm methodologies for engineering design optimization. In Proceedings of the ASME Design Engineering Technical Conference. PARTS A AND B ed. Vol. 5. 2009. p. 507-516 https://doi.org/10.1115/DETC2009-87237
Rao, Singiresu S ; Annamdas, Kiran K. / Particle swarm methodologies for engineering design optimization. Proceedings of the ASME Design Engineering Technical Conference. Vol. 5 PARTS A AND B. ed. 2009. pp. 507-516
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