Fuzzy multi-objective optimisation approach for rod shape design in long product rolling

Lecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science)

Volumn 2715, Issue , 2003, Pages 636-643

  Oduguwa, Victor ^a   Roy, Rajkumar ^a   Farrugia, Didier ^b  

^a CRANFIELD UNIVERSITY   (United Kingdom)

^b SWINDEN TECHNOLOGY CENTRE   (Netherlands)

Author keywords

[No Author keywords available]

Indexed keywords

EVOLUTIONARY ALGORITHMS; FUZZY SETS; MEMBERSHIP FUNCTIONS; OPTIMIZATION; SET THEORY; ALGORITHMS; ECONOMIC AND SOCIAL EFFECTS; FUNCTION EVALUATION; FUZZY SYSTEMS; HEALTH; PRODUCT DESIGN;

FUZZY FITNESS; FUZZY MULTI-OBJECT OPTIMIZATION; OPTIMAL ROD SHAPES; ROD SHAPE DESIGN;

FUZZY CONTROL; MULTIOBJECTIVE OPTIMIZATION;

AUTOMATIC GENERATION; DECEPTIVE PROBLEM; DEGREE OF MEMBERSHIP; FITNESS ASSIGNMENT; FITNESS EVALUATIONS; FITNESS TECHNIQUES; OPTIMAL SOLUTIONS; SHAPE OPTIMISATION;

EID: 7044232942     PISSN: 03029743     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1007/3-540-44967-1_76     Document Type: Conference Paper

References (10)

1. Shivpuri, R. and Kini, S. Application of Fuzzy Reasoning Techniques for Roll Pass Design Optimisation, Proceedings of the 39th Mechanical Working and Steel Processing Conference and Symposium on New Metal Forming Processes. 1998. p. 755-763.
2. Hur, Y. and Rhee, D. Application of fuzzy logic for automatic shape control in stainless steel rolling process, Joint 9th IFSA World Congress and 20th NAFIPS International Conference. 2001. p. 251 -256.
3. Pataro, C., D, M, and Helman, H. Direct determination of sequences of passes for the strip rolling process by means of fuzzy logic rules, Proceedings of the Second International Conference on Intelligent Processing and Manufacturing of Materials. IPMM '99. 1999. p. 549 -554.
4. Shibata, T. and Fukuda, T. Intelligent motion planning by genetic algorithm with fuzzy critic, Proceedings of the 1993 Intelligent Symposium on Intelligent Control. 1993. Chicago, IIIinois. p. 565-570.
5. Koskimaki, E. and Goos, J. Fuzzy Fitness Function for Electric machine Design by Genetic Algorithm, Proceedings of the Second Nordic Workshop on Genetic Algorithms and Their Applications (2NWGA). 1996. Vaasa, Finland. p. 237-244.
6. Bhandari, D., Pal, S.K., and Kundu, M.K. Image enhancement incorporating fuzzy fitness function in genetic algorithms, Proceedings of the Second International Conference on Fuzzy Systems,. 1993. San Francisco, U.S.A. p. 1408-1413.
7. Roy, R., Adaptive Search and the Preliminary Design of Gas Turbine Blade Cooling System, PhD Thesis, 1997, University of Plymouth: Plymouth.
8. Deb, K., Agrawal, S., Pratap, A., and Meyarivan, T. A Fast Elitist Non-dominated Sorting Genetic Algorithm for Multi-objective Optimization: NSGA-II, Parallel Problem Solving from Nature VI (PPSN-VI). 2000. p. 849-858.
9. Oduguwa, V. and Roy, R. Multi-Objective Optimisation of Rolling Rod Product Design using Meta-Modelling Approach, Proceedings of the Genetic and Evolutionary Computation Conference (GECCO-2002). 2002. New York: Morgan Kaufmann Publishers, San Francisco, USA. p. 1164-1171.
10. Oduguwa, V., Roy, R., Watts, G., Wadsworth, J., and Farrugia, D. Comparison of Low-Cost Response Surface Models for Rod Rolling Design Problems, 18th National Conference on Manufacturing Research. 2002. Leeds Metropolitan University, UK: Professional Engineering Publishing. p. 209-213.