A computational study of three demon algorithm variants for solving the traveling salesman problem

Operations Research/ Computer Science Interfaces Series

Volumn 21, Issue , 2003, Pages 155-175

  Chandran, Bala ^a   Golden, Bruce ^a   Wasil, Edward ^b  

^a UNIVERSITY OF MARYLAND   (United States)

^b AMERICAN UNIVERSITY   (United States)

Author keywords

Demon algorithm; Traveling salesman problem

Indexed keywords

EID: 84888816253     PISSN: 1387666X     EISSN: None     Source Type: Book Series    
DOI: 10.1007/978-1-4615-1043-7     Document Type: Article

References (18)

1. G. Box and M. Muller. A note on the generation of normal deviates. Annals of Mathematical Statistics, 29:610-611, 1958.
2. G. Clarke and J. Wright. Scheduling of vehicles from a central depot to a number of delivery points. Operations Research, 12(4):568-581, 1964.
3. M. Creutz. Microcanonical Monte Carlo simulation. Physical Review Letters, 50(19):1411-1414, 1983.
4. G. Dueck. New optimization heuristics: The great deluge algorithm and the record-to-record travel. Journal of Computational Physics, 104:86-92, 1993.
5. G. Dueck and T. Scheuer. Threshold accepting: A general purpose optimization algorithm appearing superior to simulated annealing. Journal of Computational Physics, 90:161-175, 1990.
6. B. Golden, J. Pepper, and T. Vossen. Using genetic algorithms for setting parameter values in heuristic search. In Intelligent Engineering Systems through Artificial Neural Networks, volume 8, pages 239-245, New York, 1998. ASME Press.
7. S. Kirkpatrick, C. Gelatt, and M. Vecchi. Optimization by simulated annealing. Science, 220:671-680, 1983.
8. S. Lin. Computer solutions of the traveling salesman problem. The Dell System Technical Journal, 44:2245-2269, 1965.
9. N. Metropolis, A. Rosenbluth, M. Rosenbluth, A. Teller, and E. Teller. Equation of state calculations by fast computing machines. Journal of Chemical Physics, 21:1087-1092, 1953.
10. I. Osman and J. Kelly. Meta-heuristics: An overview. In I. Osman and J. Kelly, editors, Meta-heuristics: Theory and Applications, pages 1-21, Boston, MA, 1996. Kluwer Academic Publishers.
11. J. Pepper. A computational study of annealing-based heuristics for the traveling salesman problem. Master's thesis, R. H. Smith School of Business, University of Maryland, College Park, 1999.
12. J. Pepper, B. Golden, and E. Wasil. Solving the traveling salesman problem with annealing-based heuristics: A computational study. IEEE Transactions on Systems, Man, and Cybernetics A, 32(l):72-77, 2002.
13. C. Reeves. Modern Heuristic Techniques for Solving Combinatorial Problems. Halstead Press, New York, 2002.
14. G. Reinelt. TSPLIB - A traveling salesman problem library. ORS A Journal on Computing, 3(4):376-384, 1991.
15. C. Ribeiro and P. Hansen, editors. Essays and Surveys in Metaheuristics. Kluwer, Boston, 2001.
16. S. Vo/3. Metaheuristics: The state of the art. In A. Nareyek, editor, Local Search for Planning and Scheduling, volume 2148 of Lecture Notes in Computer Science, pages 1-23, Heidelberg, 2001. Springer.
17. I. Wood and T. Downs. Demon algorithms and their application to optimization problems. In IEEE World Congress on Computational Intelligence, pages 1661-1666, New York, 1998. IEEE.
18. th Australian Conference on Neural Networks, Brisbane, Australia, 1998.