Crossref Citations
This article has been cited by the following publications. This list is generated based on data provided by
Crossref.
Krishnamachari, Bhaskar
Xie, Xi
Selman, Bart
and
Wicker, Stephen
2000.
Principles and Practice of Constraint Programming – CP 2000.
Vol. 1894,
Issue. ,
p.
278.
Aarts, Emile
and
Korst, Jan
2002.
Essays and Surveys in Metaheuristics.
Vol. 15,
Issue. ,
p.
1.
Ohlmann, Jeffrey W.
Bean, James C.
and
Henderson, Shane G.
2004.
Convergence in Probability of Compressed Annealing.
Mathematics of Operations Research,
Vol. 29,
Issue. 4,
p.
837.
Dorea, C. C. Y.
Martins Neto, D. S. B.
and
Pereira, A. G. C.
2004.
Sufficient Conditions for Ergodicity and Convergence of MH, SA, and EM Algorithms.
Stochastic Models,
Vol. 20,
Issue. 2,
p.
193.
Jansen, Thomas
and
Wegener, Ingo
2006.
On the local performance of simulated annealing and the (1+1) evolutionary algorithm.
p.
469.
Meiri, Ronen
and
Zahavi, Jacob
2006.
Using simulated annealing to optimize the feature selection problem in marketing applications.
European Journal of Operational Research,
Vol. 171,
Issue. 3,
p.
842.
Couceiro, I.
París, J.
Martínez, S.
Colominas, I.
Navarrina, F.
and
Casteleiro, M.
2016.
Structural optimization of lattice steel transmission towers.
Engineering Structures,
Vol. 117,
Issue. ,
p.
274.
Cruz, Juan Alberto Rojas
and
Diniz, Iesus C.
2019.
On Weak and Strong Ergodicity.
Journal of Statistical Theory and Practice,
Vol. 13,
Issue. 2,
Couceiro, I.
París, J.
Martínez, S.
Navarrina, F.
and
Colominas, I.
2021.
Computer software for analysis and design optimization of power transmission structures by simulated annealing and sensitivity analysis.
Engineering with Computers,
Vol. 37,
Issue. 4,
p.
3649.
Maity, Arnab Kumar
and
Basu, Sanjib
2023.
Highest Posterior Model Computation and Variable Selection via Simulated Annealing.
The New England Journal of Statistics in Data Science,
p.
200.
Chai, Huabin
Xu, Mingtao
Guan, Pengju
Ding, Yahui
Xu, Hui
and
Zhao, Yuqiao
2023.
Research on Mining Subsidence Prediction Parameter Inversion Based on Improved Modular Vector Method.
Applied Sciences,
Vol. 13,
Issue. 24,
p.
13272.