Hybrid genetic algorithm and simulated annealing approach for the optimization of process plans for prismatic parts

International Journal of Production Research

Volumn 40, Issue 8, 2002, Pages 1899-1922

  Li, W D ^a   Ong, S K ^a   Nee, A Y C ^a  

^a NATIONAL UNIVERSITY OF SINGAPORE   (Singapore)

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTER AIDED ANALYSIS; COMPUTER AIDED MANUFACTURING; COSTS; CUTTING TOOLS; GENETIC ALGORITHMS; OPTIMIZATION; PERFORMANCE; SIMULATED ANNEALING; TECHNICAL PRESENTATIONS;

PROCESS PLANS;

MACHINING;

EID: 0037141357     PISSN: 00207543     EISSN: None     Source Type: Journal    
DOI: 10.1080/00207540110119991     Document Type: Article

References (18)

1. Integration of design and manufacturing: Solving set-up generation and feature sequencing using an unsupervised-learning approach
2. Setup planning using Hopfield net and simulated annealing
3. Feature-based approach for set-up minimization of process design from product design
4. Genetic neuro-scheduler for job shop scheduling
5. What is manufacturing interaction?
6. Incorporating problem specific knowledge into genetic algorithms
7. Feature-based operation sequence generation in CAPP
8. A CAPP system for nonlinear process plans
9. An integrated approach to determining the sequence of machining operations for prismatic parts with interacting features
10. Application of fuzzy set theory to set-up planning
11. STEP-based integration of feature recognition and design-by-feature for manufacturing applications in a concurrent engineering environment
12. A GA-based approach to machining operation sequencing for prismatic parts
13. Operation sequencing in CAPP using genetic algorithms
14. A knowledge-based approach to automated machining process selection and sequencing
15. A genetic algorithm application for sequencing operations in process planning for parallel machining
16. Using genetic algorithms in process planning for job shop machining