A multi-agent approach to fixture design

Journal of Intelligent Manufacturing

Volumn 12, Issue 1, 2001, Pages 31-42

  Subramaniam, V ^a   Senthil Kumar, A ^a   Seow, K C ^a  

^a NATIONAL UNIVERSITY OF SINGAPORE   (Singapore)

Author keywords

Back propagation; Fixture design; Genetic algorithms; Multiple agents; Neural networks

Indexed keywords

BACKPROPAGATION; GENETIC ALGORITHMS; LEARNING SYSTEMS; MULTI AGENT SYSTEMS; NEURAL NETWORKS; OPTIMIZATION; SYSTEMS ANALYSIS;

FIXTURE DESIGNER; FIXTURE EVALUATOR; MULTI-AGENT FIXTURE DESIGN SYSTEM; MULTIPLE AGENTS;

FIXTURES (TOOLING);

EID: 0035272814     PISSN: 09565515     EISSN: None     Source Type: Journal    
DOI: 10.1023/A:1008947413133     Document Type: Article

References (14)

1. Genetic algorithms as heuristics for optimizing ANN design
2. M.L.P. optimal topology via genetic algorithms
3. Literature database on application of artificial intelligent methods in manufacturing engineering
4. Genetic weights optimization of a feedforward neural network controller
5. Intelligent hybrid system: Issues, classifications and future directions
6. Neural network weights selection using genetic algorithms
7. Genetic search for optimal representation in neural networks
8. Conceptual design using GA. Accepted for publication
9. Genetic local search algorithms for the travelling salesman problem