Auto-tuning strategy for evolutionary algorithms: Balancing between exploration and exploitation

Soft Computing

Volumn 13, Issue 2, 2009, Pages 157-168

  Lin, Lin ^a   Gen, Mitsuo ^a  

^a WASEDA UNIVERSITY   (Japan)

Author keywords

Auto tuning strategy; Evolutionary algorithms; Fuzzy logic control

Indexed keywords

EID: 55549088896     PISSN: 14327643     EISSN: 14337479     Source Type: Journal    
DOI: 10.1007/s00500-008-0303-2     Document Type: Conference Paper

References (47)

1. Altiparmak F, Gen M, Dengiz B, Smith AE (2004) A network-based genetic algorithm for design of communication networks. J Soc Plant Eng Jpn 15(4): 184-190
2. Ahn CW, Ramakrishna R (2002) A genetic algorithm for shortest path routing problem and the sizing of populations. IEEE Trans Evol Comput 6(6): 566-579
3. Beasley JE, Christofides N (1989) An algorithm for the resource constrained shortest path problem. Networks 19: 379-394
4. Bonabeau E, Dorigo M, Theraulaz G (1999) Swarm intelligence: From natural to artificial systems. Oxford University Press, New York
5. Chatterjee A, Siarry P (2006) Nonlinear inertia variation for dynamic adaptation in particle swarm optimization. Comput Oper Res 33(3): 859-871
6. Clerc M (2006) Particle swarm optimization. ISTE
7. Cheong F, Lai R (2000) Constraining the optimization of a fuzzy logic controller using an enhanced genetic algorithm. IEEE Trans Syst Man Cyber B Cybern 30(1): 31-46
8. Davis L (ed) (1991) In: Handbook of genetic algorithms. Van Nostrand Reinhold, New York
9. Dengiz B, Altiparmak F, Smith AE (1997) Efficient optimization of all-terminal reliable networks using an evolutionary approach. IEEE Trans Reliability 46: 18-26
10. Deb K (2001) Multiobjective optimization using evolutionary algorithms. Wiley, Chichester
11. Dorigo M (1992) Optimization, learning and natural algorithms, PhD thesis. Politecnico di Milano, Italy
12. Dorigo M, Stutzle T (2004) Ant colony optimization. MIT Press, Cambridge
13. Fogel L, Owens A, Walsh M (1966) Artificial intelligence through simulated evolution. Wiley, New York
14. Gen M, Cheng R (1997) Genetic algorithms and engineering design. Wiley, New York
15. Gen M, Cheng R (2000) Genetic algorithms and engineering optimization. Wiley, New York
16. Gen M, Lin L (2005) Priority-based genetic algorithm for shortest path routing problem in OSPF. In: Proceedings of GECCO, Washington, D.C., USA
17. Goldberg D (1989) Genetic algorithms in search, optimization and machine learning. Addison-Wesley, Reading
18. Herrera F, Lozano M (1996) Adaptation of genetic algorithm parameters based on fuzzy logic controllers. In: Herrera F, Verdegay J (eds) Genetic algorithms and soft computing, Physica-Verlag, pp 95-125
19. Hinterding R, Michalewisz Z, Eiben A (1997) Adaptation in evolutionary computation: A survey. Proceedings of IEEE international conference on Evol. Computat., Piscataway, 65-69
20. Holland J (1992) Adaptation in natural and artificial system. University of Michigan Press, Ann Arbor, 1975. MIT Press, Cambridge
21. Hong TP, Wang HS (1996) A dynamic mutation genetic algorithm. Proc IEEE Int Conf Syst Man Cybern 3: 2000-2005
22. Hong TP, Wang HS, Lin WY, Lee WY (2002) Evolution of appropriate crossover and mutation operators in a genetic process. Appl Int 16: 7-17
23. Ishibuchi H, Murata T (1998) A multiobjective genetic local search algorithm and its application to flowshop scheduling. IEEE Trans Syst Man Cyber 28(3): 392-403
24. Julstrom B (1995) What have you done for me lately? Adapting operator probabilities in a steady-state genetic algorithm. Proceedings of the 6th international conference on GAs, San Francisco, pp 81-87
25. Koza JR (1992) Genetic Programming. MIT Press, Cambridge
26. Koza JR (1994) Genetic Programming II. MIT Press, Cambridge
27. Koumousis VK, Katsaras CP (2006) A saw-tooth genetic algorithm combining the effects of variable population size and reinitialization to enhance performance. IEEE Trans Evol Comput 10(1): 19-28
28. Lin L, Gen M (2006a) Bicriteria network design problem using interactive adaptive-weight GA and priority-based encoding method. IEEE Trans Evol Comput (submitting)
29. Lin L, Gen M (2006b) A self-control genetic algorithm for reliable communication network design. In: Proceedings of IEEE Congress on Evolutionary Computation, pp 2655-2662
30. Michael CM, Stewart CV, Kelly RB (1991) Reducing the search time of a steady state genetic algorithm using the immigration operator. In: Proceedings of IEEE international conference tools for AI, San Jose, pp 500-501
31. Michalewicz Z (1994) Genetic algorithm + data Structures = evolution programs. Springer, New York
32. Mathias KE, Whitley LD, Stork C, Kusuma T (1994) Staged hybrid genetic search for seismic data imaging. In: Proceedings of the evolutionary computation, pp 356-361
33. Mak KL, Wong YS, Wang XX (2000) An adaptive genetic algorithm for manufacturing cell formation. Int J Manuf Technol 16: 491-497
34. OR-Library. [Online]. Available: http://people.brunel.ac.uk/~mastjjb/jeb/ info.html
35. Rechenberg I (1973) Optimieriung technischer Systeme nach Prinzipien der biologischen Evolution. Frommann-Holzboog, Stuttgart
36. Renders JM, Flasse SP (1996) Hybrid methods using genetic algorithms for global optimization. IEEE Trans Syst Man Cybern B Cybern 26(2): 243-258
37. Rogers D (1991) G/SPLINES: A hybrid of Friedman's multivariate adaptive regression splines (MARS) algorithm with Holland's genetic algorithm. In: Proceedings of the 4th international conference on genetic algorithms, pp 384-391
38. Schwefel H (1995) Evolution and optimum seeking. Wiley, New York
39. Srinvas M, Patnaik LM (1994) Adaptive probabilities of crossover and mutation in genetic algorithms. IEEE Trans Syst Man Cybern 24(4): 656-667
40. Song YH, Wang GS, Wang PT, Johns AT (1997) Environmental/economic dispatch using fuzzy logic controlled genetic algorithms. IEEE Proc Gener Transm Distrib 144(4): 377-382
41. Souza PS, Talukdar SN (1991) Genetic algorithm in asynchronous teams. In: Proceedings of the 4th international conference on genetic algorithms, pp 392-397
42. Subbu R, Sanderson AC, Bonissone PP (1998) Fuzzy logic controlled genetic algorithms versus tuned genetic algorithms: An Agile manufacturing application. In: Proceedings of the 1999 IEEE international symposium on intelligent control (ISIC), pp 434-440
43. Wang PT, Wang GS, Hu ZG (1997) Speeding up the search process of genetic algorithm by fuzzy logic. In: Proceedings of the 5th European congress on intelligent techniques and soft computing, pp 665-671
44. Wu QH, Cao YJ, Wen JY (1998) Optimal reactive power dispatch using an adaptive genetic algorithm. Electr Power Eng Syst 20(8): 563-569
45. Yun YS (2002) Hybrid genetic algorithm reinforced by fuzzy logic controller. J Korea Inst Ind Eng 28(1): 76-86
46. Yun YS, Gen M (2003) Performance analysis of adaptive genetic algorithms with fuzzy logic and heuristics. Fuzzy Optim Decis Mak 2(2): 161-175
47. Zitzler E, Thiele L (1999) Multiobjective evolutionary algorithms: A comparative case study and the strength Pareto approach. IEEE Trans Evol Comput 4(3): 257-271