Assembly planning is one of the NP complete problems, which is even more difficult to solve for complex products. Intelligent optimization algorithms have obvious advantages to deal with such combinatorial problems. Various intelligent optimization algorithms have been applied to assembly sequence planning and optimization in the last decade. This paper surveys the state-of-the-art of the assembly planning methods based on the intelligent optimization algorithms. Five intelligent optimization algorithms, i.e. genetic algorithm (GA), artificial neural networks (ANN), simulated annealing (SA), ant colony algorithm (ACO) and artificial immune algorithm (AIA), and their applications in assembly planning and optimization are introduced respectively. The application features of the algorithms are summarized. At last, the future research directions of the assembly planning based on the intelligent optimization algorithms are discussed.
Skip Nav Destination
ASME 2008 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference
August 3–6, 2008
Brooklyn, New York, USA
Conference Sponsors:
- Design Engineering Division and Computers in Engineering Division
ISBN:
978-0-7918-4327-7
PROCEEDINGS PAPER
A Survey of Assembly Planning Based on Intelligent Optimization Algorithms Available to Purchase
Sen Zeng
Sen Zeng
Beihang University, Beijing, China
Search for other works by this author on:
Jihong Liu
Beihang University, Beijing, China
Sen Zeng
Beihang University, Beijing, China
Paper No:
DETC2008-49445, pp. 1135-1141; 7 pages
Published Online:
July 13, 2009
Citation
Liu, J, & Zeng, S. "A Survey of Assembly Planning Based on Intelligent Optimization Algorithms." Proceedings of the ASME 2008 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. Volume 3: 28th Computers and Information in Engineering Conference, Parts A and B. Brooklyn, New York, USA. August 3–6, 2008. pp. 1135-1141. ASME. https://doi.org/10.1115/DETC2008-49445
Download citation file:
11
Views
Related Proceedings Papers
Related Articles
The Merits of a Parallel Genetic Algorithm in Solving Hard Optimization Problems
J Biomech Eng (February,2003)
Socio-Inspired Multi-Cohort Intelligence and Teaching-Learning-Based Optimization for Hydraulic Fracturing Parameters Design in Tight Formations
J. Energy Resour. Technol (July,2022)
Related Chapters
A Review on Using of Quantum Calculation Techniques in Optimization of the Data System of Mutation Test and its Comparison with Normal Genetic Algorithm and Bacteriological
International Conference on Computer Technology and Development, 3rd (ICCTD 2011)
Improved Method of GA's Initiation Population Based on Local-Effective-Information for Solving TSP
International Conference on Information Technology and Management Engineering (ITME 2011)
YPLC- Based Embedded Intelligent Control Research
International Conference on Mechanical and Electrical Technology, 3rd, (ICMET-China 2011), Volumes 1–3