Abstract
This work explores different evolutionary approaches to Protein Structure Prediction (PSP), a highly constrained problem. These are the utilization of a repair procedure, and the use of evolutionary operators whose functioning is closed in feasible space. Both approaches rely on hybridizing the evolutionary algorithm (EA) with a backtracking algorithm. The so-obtained hybrid EAs are described, and empirically compared to a penalty-based EA. The utilization of the repair procedure reveals itself as a very appropriate technique for tackling this problem.
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Cotta, C. (2003). Protein Structure Prediction Using Evolutionary Algorithms Hybridized with Backtracking. In: Mira, J., Álvarez, J.R. (eds) Artificial Neural Nets Problem Solving Methods. IWANN 2003. Lecture Notes in Computer Science, vol 2687. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-44869-1_41
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DOI: https://doi.org/10.1007/3-540-44869-1_41
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