A novel hybrid immune algorithm for global optimization in design and manufacturing

Robotics and Computer-Integrated Manufacturing

Volumn 25, Issue 2, 2009, Pages 261-270

  Yildiz, Ali Riza ^a  

^a ULUDAG UNIVERSITY   (Turkey)

Author keywords

Design optimization; Hill climbing; Hybrid approach; Immune algorithm; Milling operation

Indexed keywords

DESIGN OPTIMIZATION; HILL CLIMBING; HYBRID APPROACH; IMMUNE ALGORITHM; MILLING OPERATION;

DESIGN; GLOBAL OPTIMIZATION; INDUSTRIAL RESEARCH; LEARNING ALGORITHMS; MACHINING CENTERS; MILLING (MACHINING);

OPTIMIZATION;

EID: 63749123634     PISSN: 07365845     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.rcim.2007.08.002     Document Type: Article

References (48)

1. Taylor F.W. On the art of cutting metals. Trans Am Soc Mech Eng 28 31 (1907)
2. Dereli T., Filiz I.H., and Baykasoglu A. Optimizing cutting parameters in process planning of prismatic parts by using genetic algorithms. Int J Prod Res 39 15 (2001) 3303-3328
3. Wang Z.G., Rahman M., Wong Y.S., and Sun J. Optimization of multi-pass milling using parallel genetic algorithm and parallel genetic simulated annealing. Int J Mach Tools Manuf 45 15 (2005) 1726-1734
4. Petropoulos P.G. Optimal selection of machining rate variable by geometric programming. Int J Prod Res 11 4 (1973) 305-314
5. Agapiou J.S. The optimisation of machining operations based on a combined criterion. Part 2: Multipass operations. J Eng Ind 114 (1992) 508-513
6. Armarego E.J.A. Computer-aided constrained optimisation analyses and strategies for multipass helical tooth milling operation. Ann CIRP 43 1 (1994) 437-442
7. Shin Y.C., and Joo Y.S. Optimization of machining conditions with practical constraints. Int J Prod Res 30 12 (1992) 2907-2919
8. Gupta R., Batra J.L., and Lal J.K. Determination of optimal subdivision of depth of cut in multi-pass turning with constraints. Int J Prod Res 33 (1995) 115-127
9. Tolouei-Rad M., and Bidhendi I.M. On the optimization of machining parameters for milling operations. Int J Mach Tools Manuf 37 1 (1997) 1-16
10. Wang J. Computer-aided economic optimization of end-milling operations. Int J Prod Econ 54 3 (1998) 307-320
11. Wang J., and Armarego J.A. Computer-aided optimization of multiple constraint single pass face milling operations. Mach Sci Technol 5 1 (2001) 77-99
12. Wang J., Kuriyagawa T., Wei X.P., and Guo D.M. Optimization of cutting conditions for single pass turning operations using a deterministic approach. Int J Mach Tools Manuf 42 9 (2002) 1023-1033
13. Kilic S.E., Cogun C., and Sen D.T. A computer-aided graphical technique for the optimization of machining conditions. Comput Ind 22 3 (1993) 319-326
14. Bauma L.E., Mcphee J.J., and Calamai P.H. Application of genetic algorithms to the design optimization of an active vehicle suspension system. Comput Methods Appl Mech Eng 163 1-4 (1998) 87-94
15. Shunmugam M.S., Reddy S.V.B., and Narendran A.A. Selection of optimal conditions in multi-pass face-milling using a genetic algorithm. Int J Mach Tools Manuf 40 3 (2000) 401-414
16. Tandon V., El-Mounayri H., and Kishawy H. NC end milling optimization using evolutionary computation. Int J Mach Tools Manuf 42 5 (2002) 595-605
17. Holland H.J. Adaptation in natural and artificial systems: an introductory analysis with application to biology control and artificial intelligence (1975), The University of Michigan Press, Ann Arbor, USA
18. Chung J.S., and Hwang S.M. Application of a genetic algorithm to the optimal design of the die shape in extrusion. J Mater Process Technol 72 1 (1997) 69-77
19. Renders J, Bersini H. Hybridizing genetic algorithms with hill-climbing methods for global optimization: two possible ways. In: Proceedings of the first IEEE conference on evolutionary computation, Orlando, FL, 1994.
20. Yen J, Liao JC, Randolph D, Lee B. A hybrid approach to modeling metabolic systems using genetic algorithm and simplex method. In: Proceedings of the 11th IEEE conference on artificial intelligence for applications, CAIA95, Los Angeles, CA, 1995.
21. Okamoto M., Nonaka T., Ochiai S., and Tominaga D. Nonlinear numerical optimization with use of a hybrid genetic algorithm incorporating the modified Powell method. Appl Math Comput 91 1 (1997) 63-72
22. Yi{dotless}ldi{dotless}z A.R., Özturk N., Kaya N., and Özturk F. Hybrid multi-objective shape design optimization using Taguchi's method and genetic algorithm. Struct Multidiscipl Optim 34 4 (2007) 277-365
23. Yildiz A.R., and Ozturk F. Hybrid enhanced genetic algorithm to select optimal machining parameters in turning operation. Proc Inst Mech Eng B: J Eng Manuf 220 12 (2006) 2041-2053
24. Coello C.A.C., and Cortes N.C. Hybridizing a genetic algorithm with an artificial immune system for global optimization. Eng Optim 36 5 (2004) 607-634
25. Liu Y.M., and Wang C.J. A modified genetic algorithm based optimization of milling parameters. Int J Adv Manuf Technol 15 11 (1999) 796-799
26. Wang Z.G., Wong Y.S., and Rahman M. Optimisation of multi-pass milling using genetic algorithm and genetic simulated annealing. Int J Adv Manuf Technol 24 9-10 (2004) 727-732
27. Machinability Data Center. Machining data handbook. Vol. 1, 3rd ed. OH: Machinability Data Center; 1980.
28. De Castro LN, Von Zuben FJ. Artificial immune systems, part 1, Basic theory and applications. Technical report TR-DCA 01/99, 1999.
29. De Castro L.N., and Von Zuben F.J. Learning and optimization using the clonal selection principle. IEEE Trans Evol Comput 6 3 (2002) 239-251
30. De Castro LN, Von Zuben FJ. The clonal selection algorithm with engineering applications. In: Proceedings of the workshop on GECCO 2000, Las Vegas, July 2000.
31. De Castro L.N., and Timmis J.I. Artificial immune systems as a novel soft computing paradigm. Soft Comput 7 8 (2003) 526-544
32. Khoo L.P., and Alisantoso D. Line balancing of PCB assembly line using immune algorithms. Eng Comput 19 2-3 (2003) 92-100
33. Luh G.C., and Chueh C.H. Multi-modal topological optimization of structure using immune algorithm. Comput Methods Appl Mech Eng 193 36-38 (2004) 4035-4055
34. Luh G.C., and Chueh C.H. Multi-objective optimal design of truss structure with immune algorithm. Comput Struct 82 11-12 (2004) 829-844
35. Luh G.C., Chueh C.H., and Liu W.W. MOIA: multi-objective immune algorithm. Eng Optim 35 2 (2003) 143-164
36. Du H.F., Gong M.G., and Jiao L.C. A novel algorithm of artificial immune system for high-dimensional function numerical optimization. Prog Nat Sci 15 5 (2005) 463-471
37. Hajela P., and Yoo J.S. Immune network modelling in design optimization. In: Corne D., Dorigo M., and Glover F. (Eds). New ideas in optimization (1999), McGraw-Hill, New York 167-183
38. Chan F.T.S., Swarnkar R., and Tiwari M.K. Fuzzy goal-programming model with an artificial immune system (AIS) approach for a machine tool selection and operation allocation problem in a flexible manufacturing system. Int J Prod Res 43 19 (2005) 4147-4163
39. Deb K, Pratap A, Meyarivan T. Constrained test problems for multi-objective evolutionary optimization. In: Proceedings of the first international conference on evolutionary multi-criterion optimization, EMO2001, 2001.
40. Coello C.A.C., and Cortes N.C. Solving multiobjective optimization problems using an artificial immune system. Genet Programm Evol Mach 6 2 (2005) 163-190
41. Michalewicz Z, Attia, N. Evolutionary optimization of constrained problems. In: Proceedings of the 3rd annual conference on evolutionary programming. Singapore: World Scientific; 1994. p. 98-108.
42. Hadj-Alouane A.B., and Bean J.C. A genetic algorithm for the multiple-choice integer program. Oper Res 45 (1997) 92-101
43. Koziel S., and Michalewicz Z. Evolutionary algorithms, homomorphous mappings, and constrained parameter optimization. Evol Comput 7 1 (1999) 19-44
44. Hamida SB, Schoenauer M. ASCHEA: new results using adaptive segregational constraint handling. In: Proceedings of the congress on evolutionary computation, 2002, vol. 1. p. 884-9.
45. Coello C.A.C., and Christiansen A.D. MOSES: a multiple objective optimization tool for engineering design. J Eng Optim 31 3 (1999) 337-368
46. Baykasoglu A. Applying multiple objective tabu search to continuous optimization problems with a simple neighbourhood strategy. Int J Num Methods Eng 65 (2006) 406-424
47. Eschenauer H., Koski J., and Osyczka A. Multicriteria design optimization (1990), Springer, Berlin
48. Coello CAC. An empirical study of evolutionary techniques for multiobjective optimization in engineering design. PhD thesis, Department of Computer Science, Tulane University, New Orleans, LA, 1996.