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The N-City Travelling Salesman Problem: Statistical Mechanics and the Metropolis Algorithm
Open accessAbstract
In any N-city travelling salesman problem there are $(N - 1){! \mathord{\left/ {\vphantom {! 2}} \right. \kern-\nulldelimiterspace} 2}$ possible tours. We use the Metropolis algorithm to generate a sequence of such tours. This sequence may be viewed as the random evolution of a physical system in contact with a heat-bath. As the temperature is lowered, the tours generated approach the optimal tour. It appears that for large N one arrives within a few percent of the optimal solution in better than quadratic time.
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Information theory and statistical mechanics
Jaynes, E. T. (1957) · Physical Review · doi:10.1103/physrev.106.620 · Cited by 12,931
Cited by
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Generalized Simulated Annealing for Function Optimization
Bohachevsky, I. O., Johnson, M. E., & Stein, M. L. (1986) · Technometrics · doi:10.1080/00401706.1986.10488128 · Cited by 573
Bateson, C. A., Asner, G. P., & Wessman, C. A. (2000) · IEEE Transactions on Geoscience and Remote Sensing · doi:10.1109/36.841987 · Cited by 382
An evolutionary approach to the traveling salesman problem
Fogel, D. B. (1988) · Biological Cybernetics · doi:10.1007/bf00202901 · Cited by 287
Metadata
- Authors
- Bonomi, E., & Lutton, J.-L.
- Venue
- SIAM Review
- Published
- 1984-10
- Volume
- 26
- Issue
- 4
- Pages
- 551-568
- ISSN
- 0036-1445 (ISSN-L)
- 1095-7200
- OpenAlex
- W2076138782
- Cited by
- 251
- References
- 1
- FWCI
- 17.59
- Type
- journal article
- Language
- en
- Open access
- green
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