An improved genetic algorithm adopting immigration operator

Intelligent Data Analysis

Volumn 8, Issue 4, 2004, Pages 385-401

  Yang, Wen Xian ^a,b  

^a NORTHWESTERN POLYTECHNICAL UNIVERSITY   (China)

^b NOTTINGHAM TRENT UNIVERSITY   (United Kingdom)

Author keywords

genetic algorithm; immigration operator; traveling salesman problem

Indexed keywords

ENGINES; GENETIC ALGORITHMS;

BENCHMARKING PROBLEMS; CONVERGENCE PERFORMANCE; CROSSOVER OPERATOR; EXHAUST VALVES; GENETIC ALGORITHM (GAS); IMMIGRATION OPERATOR; PRICE FUNCTION; RATE OF CONVERGENCE;

TRAVELING SALESMAN PROBLEM;

EID: 33644962568     PISSN: 1088467X     EISSN: 15714128     Source Type: Journal    
DOI: 10.3233/ida-2004-8405     Document Type: Article

References (30)

1. J. Holland, Adaptation in natural and artificial systems, Ann Arbor: University of Michigan Press, 1975.
2. C. Dimopoulos and Ali M.S. Zalzala, Recent developments in evolutionary computation for manufacturing optimization: problems, solutions and comparisons, IEEE Transactions on Evolutionary Computation 4(2) (2000), 93-113.
3. B. Thomas, Ulrich hammel and Hans-Paul Schwefel, Evolutionary computation: comments on the history and current state, IEEE Transactions on Evolutionary Computation 1(1) (1997), 3-17.
4. B. Raton, Genetic algorithms for pattern recognition, CRC Press, 1996.
5. M. Shaunna, L. Tom and H. Abdulla, A genetic algorithm environment for star pattern recognition, Journal of Intelligent and Fuzzy Systems 6 (1998), 3-16.
6. P. Mars, J.R. Chen and R. Nambiar, Learning algorithms: theory and applications in signal processing, control and communications, CRC Press, 1996.
7. J. Bieyhahn and V. Nissen, Evolutionary algorithms in management applications, Springer Press, 1995.
8. L.C. Jain and N.M. Martin, Fusion of neural networks, fuzzy sets and genetic algorithms: Industrial applications, CRC Press, 1999.
9. C.C. Bojarczuk, H.S. Lopes and A.A. Freitas, Genetic programming for knowledge discovery in chest-pain diagnosis, IEEE Engineering in Medicine and Biology Magazine 19(4) (2000), 38-44.
10. M.L. Wong, W. Lam, K.S. Leung et al., Discovering knowledge from medical database using evolutionary algorithms, IEEE Engineering in Medicine and Biology Magazine 19(4) (2000), 45-55.
11. S. Tsutsui and A. Ghosh, A study on the effect of multi-parent recombination in real coded genetic algorithms, IEEE International Conference on Evolutionary Computation, Anchorage, Alaska, USA, May 1998, pp. 828-833.
12. I.D. Falco, A. Iazzetta and E. Tarantino, The effectiveness of co-mutation in evolutionary algorithms: the operator, IEEE International Conference on Evolutionary Computation, Anchorage, Alaska, USA, May 1998, pp. 816-821
13. K. Chellapilla, Combining mutation operators in evolutionary programming, IEEE Transactions on Evolutionary Computation 2(3) (1998), 91-96.
14. F. Herrera and M. Lozano, Adaptive genetic operators based on coevolution with Fuzzy behaviors, IEEE Transactions on Evolutionary Computation 5(2) (2001), 149-166.
15. H. Handa, O. Katai, N. Baba and T. Sawaragi, Solving constraint satisfaction problems by using coevolutionary genetic algorithms, IEEE International Conference on Evolutionary Computation, Anchorage, Alaska, USA, May 1998, pp. 21-26.
16. G.R. Raidl, An improved genetic algorithm for the Multi-constrained O-I Knapsack Problem, IEEE International Conference on Evolutionary Computation, Anchorage, Alaska, USA, May 1998, pp. 207-211.
17. A.R. Andino, Lourdes Araujo, Fernando Saenz and Jose Ruz, A hybrid evolutionary approach for solving constrained optimization problems over finite domains, IEEE Transactions on Evolutionary Computation 4(4) (2000), 353-372.
18. G. Magyar, Mika Johnsson and Olli Nevalainen, An adaptive hybrid genetic algorithm for the three matching problem, IEEE Transactions on Evolutionary Computation 4(2) (2000), 135-146.
19. G. Bilchev and H.S. Olafsson, Comparing genetic algorithms and greedy heuristics for adaption problems, IEEE International Conference on Evolutionary Computation, Anchorage, Alaska, USA, May 1998, pp. 458-463.
20. B.L. Wu and X.H. Yu, Enhanced evolutionary programming for function optimization, IEEE International Conference on Evolutionary Computation, Anchorage, Alaska, USA, May 1998, pp. 695-698.
21. Y. Nagata and S. Kobayashi, Edge assembly crossover: a high-power genetic algorithm for the travelling salesman problem, The 7th International Conference on Genetic Algorithms, Eastlansing, Mich, July 1997, pp. 450-457.
22. C.L. Valenzuela and L.P.Williams, Improving heuristic algorithms for the travelling salesman problem by using a genetic algorithm to perturb the cities, The 7th International Conference on Genetic Algorithms, Eastlansing, Mich, July 1997, pp. 458-464.
23. R. Yang, Solving large travelling salesman problems with small population, International Conference on Genetic Algorithms in Engineering Systems: Innovations and Application, University of Strathclyde, Glasgow, UK, September 1997, pp. 157-162.
24. H.J. Cho, S.Y. Oh and D.H. Choi, A new evolutionary programming approach based on simulated annealing with local cooling schedule, IEEE International Conference on Evolutionary Computation, Anchorage, Alaska, USA, May 1998, pp. 598-602.
25. D.T. Pham and D. Karaboga, Intelligent optimization techniques: genetic algorithms, tabu search, simulated annealing and neural networks, London: Springer, 2000.
26. R.K. Autar, An automated diagnostic expert system for diesel engines, Transaction of the ASME Journal of Engineering for Gas Turbines and Power 118 (1996), 673-679.
27. F. Gu, A.D. Ball and K.K. Rao, Diesel injector dynamic modelling and estimation of parameters from impact response Part 2: prediction of injection parameters from monitored vibration, Proceedings of International Mechanical Engineering Part D, Journal of Automobile Engineering 210 (1996), 303-312.
28. Y. Zhang, Z.P. Zhang and Y.C. Zhou, Research on the fuzzy and dynamic monitoring of the diesel engine operating conditions, Proceedings of International Mechanical Engineering Part D, Journal of Automobile Engineering 212 (1998), 421-426.
29. P.S. Katsoulakos, J. Newland, J.T. Stansfield and T. Ruxton, Monitoring, databases and expert systems in the development of engine fault diagnostics, British Journal of NDT 38(7) (1998), 447-452.
30. M. Nyberg, Model based fault diagnosis: methods, theory and automotive engine applications, Linkoping, Sweden, 1999.