The DOI matches its Crossref record; 18 of the 18 references it cites were found in a registry or an index.
Optimization by Simulated Annealing: An Experimental Evaluation; Part I, Graph Partitioning
Abstract
In this and two companion papers, we report on an extended empirical study of the simulated annealing approach to combinatorial optimization proposed by S. Kirkpatrick et al. That study investigated how best to adapt simulated annealing to particular problems and compared its performance to that of more traditional algorithms. This paper (Part I) discusses annealing and our parameterized generic implementation of it, describes how we adapted this generic algorithm to the graph partitioning problem, and reports how well it compared to standard algorithms like the Kernighan-Lin algorithm. (For sparse random graphs, it tended to outperform Kernighan-Lin as the number of vertices become large, even when its much greater running time was taken into account. It did not perform nearly so well, however, on graphs generated with a built-in geometric structure.) We also discuss how we went about optimizing our implementation, and describe the effects of changing the various annealing parameters or varying the basic annealing algorithm itself.
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Cites
Optimization by Simulated Annealing
Kirkpatrick, S., Gelatt, C. D., & Vecchi, M. P. (1983) · Science · doi:10.1126/science.220.4598.671 · Cited by 45,134
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Stochastic relaxation, gibbs distributions, and the bayesian restoration of images.
Geman, S., & Geman, D. (1984) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.1984.4767596 · Cited by 17,949
An Efficient Heuristic Procedure for Partitioning Graphs
Kernighan, B. W., & Lin, S. (1970) · Bell System Technical Journal · doi:10.1002/j.1538-7305.1970.tb01770.x · Cited by 5,305
Thermodynamical approach to the traveling salesman problem: An efficient simulation algorithm
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Simulated annealing: theory and applications.
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Some simplified NP-complete graph problems
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Self-citationOptimization by simulated annealing: Quantitative studies
Kirkpatrick, S. (1984) · Journal of Statistical Physics · doi:10.1007/bf01009452 · Cited by 1,805
Convergence of an annealing algorithm
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Cited by
Schaeffer, S. E. (2007) · Computer Science Review · doi:10.1016/j.cosrev.2007.05.001 · Cited by 1,639
Job Shop Scheduling by Simulated Annealing
van Laarhoven, P. J. M., Aarts, E. H. L., & Lenstra, J. K. (1992) · Operations Research · doi:10.1287/opre.40.1.113 · Cited by 1,123
Systems biology: parameter estimation for biochemical models
Ashyraliyev, M., Fomekong‐Nanfack, Y., Kaandorp, J. A., & Blom, J. G. (2009) · The FEBS Journal · doi:10.1111/j.1742-4658.2008.06844.x · Cited by 323
Benchmarking in Optimization: Best Practice and Open Issues
Bartz-Beielstein, T., Doerr, C., Berg, D. V. D., Bossek, J., Chandrasekaran, S., Eftimov, T., Fischbach, A., Kerschke, P., La Cava, W., Lopez-Ibanez, M., et al. (2020) · arXiv · doi:10.48550/arxiv.2007.03488 · Cited by 214
Using simulated annealing to design good codes
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Metadata
- Authors
- Johnson, D. S., Aragon, C. R., McGeoch, L. A., & Schevon, C.
- Venue
- Operations Research
- Published
- 1989-12
- Volume
- 37
- Issue
- 6
- Pages
- 865-892
- ISSN
- 0030-364X (ISSN-L)
- 1526-5463
- OpenAlex
- W2128193809
- Cited by
- 1,457
- References
- 18
- FWCI
- 27.66
- Type
- journal article
- Language
- en
- Open access
- closed
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- Johnson, D. S., Aragon, C. R., McGeoch, L. A., & Schevon, C. (1989). Optimization by Simulated Annealing: An Experimental Evaluation; Part I, Graph Partitioning. Operations Research. https://doi.org/10.1287/opre.37.6.865
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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