| dc.creator | Segura, Enrique Carlos | |
| dc.date | 2005-12 | |
| dc.date | 2008-05-23T03:00:00Z | |
| dc.identifier | http://sedici.unlp.edu.ar/handle/10915/9590 | |
| dc.description | In this paper a thermodynamic approach is presented to the problem of convergence of evolutionary algorithms. The case of the Simulated Annealing algorithm for optimisation is considered as a simple evolution strategy with a control parameter allowing balance between the probability of obtaining an optimal or near-optimal solution and the time that the algorithm will take to reach equilibrium. This capacity is analysed and a theoretical frame is presented, stating a general condition to be fulfilled by an evolutionary algorithm in order to ensure its convergence to a global maximum of the fitness function. | |
| dc.description | Facultad de Informática | |
| dc.format | application/pdf | |
| dc.format | 178-182 | |
| dc.language | en | |
| dc.rights | http://creativecommons.org/licenses/by-nc/3.0/ | |
| dc.rights | Creative Commons Attribution-NonCommercial 3.0 Unported (CC BY-NC 3.0) | |
| dc.subject | Ciencias Informáticas | |
| dc.subject | evolutionary computation | |
| dc.subject | simulated annealing | |
| dc.subject | thermodynamics of equilibrium | |
| dc.subject | detailed balance | |
| dc.subject | ergodicity | |
| dc.title | Evolutionary computation with simulated annealing: conditions for optimal equilibrium distribution | |
| dc.type | Articulo | |
| dc.type | Articulo | |
