论文信息 - GenAnneal: Genetically modified Simulated Annealing

GenAnneal: Genetically modified Simulated Annealing

A modification of the standard Simulated Annealing (SA) algorithm is presented for finding the global minimum of a continuous multidimensional, multimodal function. We report results of computational experiments with a set of test functions and we compare to methods of similar structure. The accompanying software accepts objective functions coded both in Fortran 77 and C++.

Isaac E. Lagaris | Ioannis G. Tsoulos

[1] Conor Ryan,et al. Grammatical evolution , 2007, GECCO '07.

[2] Michael O'Neill,et al. Grammatical evolution - evolutionary automatic programming in an arbitrary language , 2003, Genetic programming.

[3] Emile H. L. Aarts,et al. Simulated Annealing: Theory and Applications , 1987, Mathematics and Its Applications.

[4] Conor Ryan,et al. Grammatical Evolution , 2001, Genetic Programming Series.

[5] C. D. Gelatt,et al. Optimization by Simulated Annealing , 1983, Science.

[6] M. J. D. Powell,et al. A tolerant algorithm for linearly constrained optimization calculations , 1989, Math. Program..

[7] Yaroslav D. Sergeyev,et al. Algorithm 829: Software for generation of classes of test functions with known local and global minima for global optimization , 2003, TOMS.

[8] Sandro Ridella,et al. Minimizing multimodal functions of continuous variables with the “simulated annealing” algorithmCorrigenda for this article is available here , 1987, TOMS.

[9] Isaac E. Lagaris,et al. Genetically controlled random search: a global optimization method for continuous multidimensional functions , 2006, Comput. Phys. Commun..

[10] Lester Ingber,et al. Simulated annealing: Practice versus theory , 1993 .

[11] M. J. D. Powell,et al. A fast algorithm for nonlinearly constrained optimization calculations , 1978 .