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Asymptotic Convergence of Simulated Annealing

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8.7 Bibliographical Notes

  • Aarts, E.H.L., and J. Korst [1989], Simulated Annealing and Boltzmann Machines, Wiley.

    Google Scholar 

  • Albrecht, A.A. [2004], A problem-specific convergence bound for simulated annealingbased local search, Proceedings of the International Conference on Computational Science and its Applications, Assisi, Italy, 405–414.

    Google Scholar 

  • Anily, S., and A. Federgruen [1987a], Ergodicity in parametric nonstationary Markov chains: An application, Operations Research 35, 867–874.

    MathSciNet  MATH  Google Scholar 

  • Anily, S., and A. Federgruen [1987b], Simulated annealing methods with general acceptance probabilities, Journal of Applied Probability 24, 657–667.

    Article  MathSciNet  MATH  Google Scholar 

  • Drost, S., T. Jansen, and I. Wegener [2001], Dynamic parameter control in simple evolutionary algorithms, Proceedings of the 6th Workshop on Foundations of Genetic Algorithms, Charlottesville, VA, 275–294.

    Google Scholar 

  • Faigle, U., and W. Kern [1991], Note on the convergence of simulated annealing algorithms, SIAM Journal on Control and Optimization 29, 153–159.

    Article  MathSciNet  MATH  Google Scholar 

  • Feller, W. [1950], An Introduction to Probability Theory and Its Applications; Volume 1, Wiley.

    Google Scholar 

  • Hajek, B. [1988], Cooling schedules for optimal annealing, Mathematics of Operations Research 13, 311–329.

    Article  MathSciNet  MATH  Google Scholar 

  • Isaacson, D., and R. Madsen [1976], Markov Chains, Wiley.

    Google Scholar 

  • Jerrum, M., and G.B. Sorkin [1998], The Metropolis algorithm for graph bisection, Discrete Applied Mathematics 82, 155–175.

    Article  MathSciNet  MATH  Google Scholar 

  • Jerrum, M. [1992], Large cliques elude the Metropolis process, Random Structures and Algorithms 3, 347–359.

    MathSciNet  MATH  Google Scholar 

  • Kolonko, M. [1999], Some new results on simulated annealing applied to the job shop scheduling problem, European Journal of Operational Research 113, 123–136.

    Article  MATH  Google Scholar 

  • Lundy, M., and A. Mees [1986], Convergence of an annealing algorithm, Mathematical Programming 34, 111–124.

    Article  MathSciNet  MATH  Google Scholar 

  • Mitra, D., F. Romeo, and A.L. Sangiovanni-Vincentelli [1986], Convergence and finite-time behavior of simulated annealing, Advances in Applied Probability 18, 747–771.

    Article  MathSciNet  MATH  Google Scholar 

  • Motwani, R., and P. Raghavan [1995], Randomized Algorithms, Cambridge University Press.

    Google Scholar 

  • Nolte, A., and R. Schrader [1996], Simulated annealing and its problems to color graphs, Proceedings of the 4th Annual European Symposium on Algorithms, Barcelona, Spain, 138–151.

    Google Scholar 

  • Nolte, A., and R. Schrader [1997], Coloring in sublinear time, Proceedings of the 5th Annual European Symposium on Algorithms, Graz, Austria, 388–401.

    Google Scholar 

  • Nolte, A., and R. Schrader [2000], A note on the finite time behavior of simulated annealing, Mathematics of Operations Research 25, 476–484.

    Article  MathSciNet  MATH  Google Scholar 

  • Orosz, J.E., and S.H. Jacobson [2002], Finite-time performance analysis of static simulated annealing algorithms, Computational Optimization and Applications 21, 21–53.

    Article  MathSciNet  MATH  Google Scholar 

  • Sasaki, G., and B. Hajek [1988], The time complexity of maximum matching by simulated annealing, Journal of the ACM 35, 387–403.

    Article  MathSciNet  Google Scholar 

  • Seneta, E. [1981], Non-negative Matrices and Markov Chains, Springer.

    Google Scholar 

  • Sorkin, G.B. [1991], Efficient simulated annealing on fractal energy landscapes, Algorithmica 6, 367–418.

    Article  MathSciNet  MATH  Google Scholar 

  • Steinhöfel, K., A.A. Albrecht, and C.K. Wong [1998], On various cooling schedules for simulated annealing applied to the job shop problem, Proceedings of the 2nd International Workshop on Randomized and Approximation Techniques in Computer Science, Barcelona, Spain, 260–279.

    Google Scholar 

  • Wegener, I. [2005], Simulated annealing beats Metropolis in combinatorial optimization, Proceedings of the 32nd International Colloquium on Automata, Languages and Programming, Lisbon, Portugal, 589–601.

    Google Scholar 

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(2007). Asymptotic Convergence of Simulated Annealing. In: Theoretical Aspects of Local Search. Monographs in Theoretical Computer Science, An EATCS Series. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-35854-1_8

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  • DOI: https://doi.org/10.1007/978-3-540-35854-1_8

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