Abstract
Neural networks (NNs) and genetic algorithms (GAs) are the two most popular bio-inspired techniques. Criticism of these approaches includes the tendency of recurrent neural networks to produce infeasible solutions, the lack of generalize of the self-organizing approaches, and the requirement of tuning many internal parameters and operators of genetic algorithms. This paper proposes a new technique which enables feasible solutions, removes the tuning phase, and improves solutions quality of typical combinatorial optimization problems as the p-median problem. Moreover, several biology inspired approaches are analyzed for solving traditional benchmarks.
Keywords
- Genetic Algorithm
- Tabu Search
- Travel Salesman Problem
- Combinatorial Optimization Problem
- Recurrent Neural Network
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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Domínguez, E., Muñoz, J. (2005). Applying Bio-inspired Techniques to the p-Median Problem. In: Cabestany, J., Prieto, A., Sandoval, F. (eds) Computational Intelligence and Bioinspired Systems. IWANN 2005. Lecture Notes in Computer Science, vol 3512. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11494669_9
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DOI: https://doi.org/10.1007/11494669_9
Publisher Name: Springer, Berlin, Heidelberg
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