Adaptive Simulated Annealing (ASA) is a C-language code developed to statistically find the best global fit of a nonlinear constrained non-convex cost-function over a D-dimensional space. This algorithm permits an annealing schedule for ”temperature” T decreasing exponentially in annealing-time k, T = T_0 exp(-c k^1/D). The introduction of re-annealing also permits adaptation to changing sensitivities in the multi-dimensional parameter-space. This annealing schedule is faster than fast Cauchy annealing, where T = T_0/k, and much faster than Boltzmann annealing, where T = T_0/ln k. ASA has over 100 OPTIONS to provide robust tuning over many classes of nonlinear stochastic systems.

References in zbMATH (referenced in 57 articles , 1 standard article )

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  1. Valenzuela, Michael L.; Rozenblit, Jerzy W.: Learning using anti-training with sacrificial data (2016)
  2. Silva, Ricardo M.A.; Resende, Mauricio G.C.; Pardalos, Panos M.: Finding multiple roots of a box-constrained system of nonlinear equations with a biased random-key genetic algorithm (2014)
  3. Solonen, Antti: Proposal adaptation in simulated annealing for continuous optimization problems (2013)
  4. Cooren, Yann; Clerc, Maurice; Siarry, Patrick: MO-TRIBES, an adaptive multiobjective particle swarm optimization algorithm (2011)
  5. Ingber, Lester; Nunez, Paul L.: Neocortical dynamics at multiple scales: EEG standing waves, statistical mechanics, and physical analogs (2011)
  6. Xu, Jiuping; Zhou, Xiaoyang: Fuzzy-like multiple objective decision making (2011)
  7. Hilaire, Thibault; Chevrel, Philippe; Whidborne, James F.: Finite wordlength controller realisations using the specialised implicit form (2010)
  8. Tantar, Alexandru-Adrian; Melab, Nouredine; Talbi, El-Ghazali: A grid-based hybrid hierarchical genetic algorithm for protein structure prediction (2010)
  9. Chortaras, Alexandros; Stamou, Giorgos; Stafylopatis, Andreas: Definition and adaptation of weighted fuzzy logic programs (2009)
  10. Molvalioglu, Orcun; Zabinsky, Zelda B.; Kohn, Wolf: The interacting-particle algorithm with dynamic heating and cooling (2009)
  11. Oliveira, Hime A. jun.; Petraglia, Antonio; Petraglia, Mariane R.: Frequency domain FIR filter design using fuzzy adaptive simulated annealing (2009)
  12. Rocha, Ana Maria A.C.; Fernandes, Edite M.G.P.: Modified movement force vector in an electromagnetism-like mechanism for global optimization (2009)
  13. Vaz, A.I.F.; Vicente, L.N.: PSwarm: a hybrid solver for linearly constrained global derivative-free optimization (2009)
  14. Bolker, Benjamin M.: Ecological models and data in R (2008)
  15. Morgans, Rick C.; Zander, Anthony C.; Hansen, Colin H.; Murphy, David J.: EGO shape optimization of Horn-loaded loudspeakers (2008)
  16. Pedamallu, Chandra Sekhar; Ozdamar, Linet: Investigating a hybrid simulated annealing and local search algorithm for constrained optimization (2008)
  17. Sun, Shaohua; Zhuge, Feng; Rosenberg, Jarrett; Steiner, Robert M.; Rubin, Geoffrey D.; Napel, Sandy: Learning-enhanced simulated annealing: Method, evaluation, and application to lung nodule registration. (2008)
  18. Tantar, Alexandru-Adrian; Melab, Nouredine; Talbi, El-Ghazali: A grid-based genetic algorithm combined with an adaptive simulated annealing for protein structure prediction (2008)
  19. Williams, Paul: Deployment/retrieval optimization for flexible tethered satellite systems (2008)
  20. Zimmermann, Armin: Stochastic discrete event systems. Modeling, evaluation, applications. (2008)

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