Performance analysis of a new genetic crossover for the traveling salesman problem

IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences

Volumn E81-A, Issue 5, 1998, Pages 738-750

  Katayama, Kengo ^a   Hirabayashi, Hisayuki ^a   Narihisa, Hiroyuki ^a  

^a OKAYAMA UNIVERSITY OF SCIENCE   (Japan)

Author keywords

Common subtour; Complete subtoiir exchange crossover; Genetic algorithm; Traveling salesman problem

Indexed keywords

COMPUTATIONAL COMPLEXITY; MATHEMATICAL OPERATORS; OPTIMIZATION; PARALLEL PROCESSING SYSTEMS; PROBLEM SOLVING; SET THEORY; SUPERCOMPUTERS;

COMMON SUBTOUR; COMPLETE SUBTOUR EXCHANGE CROSSOVER; TRAVELING SALESMAN PROBLEM;

GENETIC ALGORITHMS;

EID: 0032066060     PISSN: 09168508     EISSN: None     Source Type: Journal    
DOI: None     Document Type: Article

References (41)

1. D.E. Goldberg, Genetic algorithms in search optimization and machine learning, Addison-Wesley, 1989.
2. Z. Michalewicz, Genetic algorithms + data structures = evolution programs, pp.11-94, pp.165-191, Springer-Verlag, New York, 1992.
3. L. Chambers, Practical handbook of genetic algorithms applications, vol.1, pp.143-172, CRC Press, Inc., 1995.
4. H. Kitano, ed., Genetic algorithms, Saneyo Tosho pub., 1993.
5. MO. Bell, T.L. Magnanti, G.L. Nemhauser, and C.L. Monma, Handbooks in operations research and management science network models, vol.7, pp.225-330, North Holland, 1995.
6. S. Lin and B.W. Kernighan, An effective heuristic algorithm for the traveling salesman problem, Operations Research, vol.21, pp.498-516, 1973.
7. D.S. Johnson, C.R. Aragon, L.A. McGeoch, and C. Schevon, Optimization by simulated annealing: An experimental evaluation; Part I, graph partitioning, Operations Research, vol.37, no.6, pp.865-892, 1989.
8. D.S. Johnson, Local optimization and the traveling salesman problem, Proc. 17th. Colloquium on Automata, Lang., and Prog., pp.446-461, Springer-Verlag, 1990.
9. D.S. Johnson and L.A. McGeoch, The traveling salesman problem: A case study, in Local Search in Combinatorial Optimization, Wiley-Interscience Series in Discrete Mathematics and Optimization, pp.215-310, 1997.
10. F. Glover, Tabu search-Part I, ORS A J. Computing, vol.1, no.3, pp. 190-206, 1989.
11. R.M. Brady, Optimization strategies gleaned from biological evolution, Nature, vol.317, pp.804-806, 1985.
12. M. Yamamura, T. Ono, and S. Kobayashi, Characterpreserving genetic algorithms for traveling salesman problem, JSAI, vol.7, no.6, pp.1049-1059, 1992.
13. M. Yamamura, I. Ono, and S. Kobayashi, Emergent search on double circle TSPs using subtour exchange crossover, Proc. 96 IEEE Int. Conf. on Evolutionary, Computation, Nagoya, Japan, pp.535-540, 1996.
14. T. Ibaraki, Combination with other optimization methods, in Handbook of Evolutionary Computation, eds. T. Back, D.B Fogel, and Z. Michalewicz, IOP Publishing Ltd and Oxford University Press, 1997.
15. M. Yagiura, H. Nagamochi, and T. Ibaraki, Two comments on the subtour exchange crossover operator, JSAI, vol.10, no.3, pp.134-137, 1995.
16. M. Yagiura and T. Ibaraki, On genetic crossover operators for sequencing problems, T. IEE Japan, vol.114-C, no.6, pp.713-720, 1994.
17. T. Uno and M. Yagiura, Fast algorithms to enumerate all common intervals of two permutations, Technical Report £96015, Department of Applied Mathematics and Physics, Graduate School of Engineering, Kyoto University, 1996.
18. M. Yagiura and T. Ibaraki, The use of dynamic programming in genetic algorithms for permutation problems, Eu-ropean Journal of Ope. Res., vol.92, pp.387-401, 1996.
19. G. Reinelt, TSPLIB, ftp://softlib.rice.edu/pub/tsplib/ tsplib.tar
20. P. Prinetto, M. Rebaudengo, and M.S. Reorda, Hybrid genetic algorithms for the traveling salesman problem, in Artificial Neural Nets and Genetic Algorithms, ed. R.F. Albrecht, pp.559-566, Springer-Verlag/Wien New York, 1993.
21. N.L.J. Ulder, E.H.L. Aarts, H.-J. Bandelt, P.J.M. van Laarhoven, and E. Pesch, Genetic local search algorithms for the traveling salesman problem, Proc. Parallel Problem Solving from Nature, eds. H.-P. Schwefel and R. Manner, pp.109-116, 1991.
22. H. Mühlenbein, M. Gorges-Schleuter, and O. Krämer, Evolution algorithms in combinatorial optimization, in Parallel Computing 7, pp.65-85, North-Holland, 1988.
23. H. Mühlenbein, Evolution in time and space-The parallel genetic algorithm, Foundations of Genetic Algorithms, ed. G. Rawlins, pp.316-337, Morgan-Kaufmann, 1991.
24. H. Mühlenbein, Parallel genetic algorithms in combinatorial optimization, in Computer Science and Operations Research, pp.441-453, Pergamon Press, 1992.
25. B. Freisieben and P. Merz, New genetic local search operators for the traveling salesman problem, Proc. Parallel Problem Solving from Nature IV, pp.890-899, 1996.
26. T. Kido, Hybrid searches using genetic algorithms, in Genetic Algorithms, ed. H. Kitano, Sangyo Tosho pub., pp.61-88, 1993.
27. T. Tajima, K. Nakano, M. Ichikawa, and H. Maeda, A real-time path planning using genetic algorithms, JSAI, vol.10, no.l, pp.94-104, 1995.
28. K. Katayama, H. Sakamoto, and H. Narihisa, An efficiency of hybrid mutation genetic algorithm for traveling salesman problem, Proc. 2nd Australia-Japan Workshop on Stochastic Models in Engineering, Technique & Management, Gold Coast, Australia, pp.294-301, 1996.
29. K. Katayama and H. Narihisa, A fast algorithm to enumerate all common subtours in complete subtour exchange crossover and the behavior property, IE1CE Trans., vol.J81-D-I, no.2, pp.213-218, Feb. 1998.
30. K. Katayama, H. Hirabayashi, and H. Narihisa, A study on parallel hybrid genetic algorithms for the traveling salesman problem, IEICE Technical Report, COMP9731, 1997.
31. B.R. Fox and M.B. McMahon, Genetic operators for sequencing problems, in Foundations of Genetic Algorithms, ed. G. Rawlins, pp.284-300, Morgan-Kaufmann, 1991.
32. J. Grefensfette, R. Gopal, B. Rosmaita, and D. Van Gucht, Genetic algorithms for the traveling salesman problem, Proc. 1st ICGA, pp.160-168, 1985.
33. P. Jog, J.Y. Suh, and D. Van Gucht, The effects of population size, heuristic crossover and local improvement on a genetic algorithm for the traveling salesman problem, Proc. 3rd ICGA, pp.110-115, 1989.
34. D. Whitley, T. Starkweather, and D. Fuquay, Scheduling problems and traveling salesman: The genetic edge recombination operator, Proc. 3rd ICGA, pp.133-140, 1989.
35. T. Starkweather, S. McDaniel, K. Mathias, D. Whitley, and C. Whitley, A comparison of genetic sequencing operators, Proc. 4th ICGA, pp.69-76, 1991.
36. K. Mathias and D. Whitley, Genetic operators, the fitness landscape and the traveling salesman problem, Proc. Parallel Problem Solving from Nature II, pp.219-228, 1992.
37. L. Homaifar, C. Guan, and G. Liepins, A new approach to the traveling salesman problem by genetic algorithm, Proc. 5th ICGA, pp.460-466, 1993.
38. J. Dzubera and D. Whitley, Advanced correlation analysis of operators for the traveling salesman problem, Proc. Parallel Problem Solving from Nature III, pp.68-77, 1994.
39. A.Y.C. Tang and K.S. Leung, A modified edge recombination operator for the traveling salesman problem, in Parallel Problem Solving from Nature III, pp.180-188, 1994.
40. Y. Nagata and S. Kobayashi, Edge assembly crossover: A high-power genetic algorithm for the traveling salesman problem, Proc. 7th ICGA, pp.450-457, 1997.
41. H. Ishibuchi, T. Murata, and S. Tomioka, Effectiveness of genetic local search algorithms, Proc. 7th ICGA, pp.505512, 1997.