Solving the Ring Loading Problem Using Genetic Algorithms with Intelligent Multiple Operators

Bernardino, Anabela M.; Bernardino, Eugénia M.; Sánchez-Pérez, Juan M.; Gómez-Pulido, Juan A.; Vega-Rodríguez, Miguel A.; Moreira Bernardino, Anabela; Bernardino, Eugénia

http://hdl.handle.net/10400.8/12819

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Solving the Ring Loading Problem Using Genetic Algorithms with Intelligent Multiple Operators.pdf	Planning optical communication networks suggests a number of new optimization problems, most of them in the field of combinatorial optimization. We address here the Ring Loading Problem. The objective of the problem is to find a routing scheme such that the maximum weighted load on the ring is minimized. In this paper we consider two variants: (i) demands can be split into two parts, and then each part is sent in a different direction; (ii) each demand must be entirely routed in either of the two directions, clockwise or counterclockwise. In this paper, we propose a genetic algorithm employing multiple crossover and mutation operators. Two sets of available crossover and mutation operators are established initially. In each generation a crossover method is selected for recombination and a mutation method is selected for mutation based on the amount fitness improvements achieve over a number of previous operations (recombinations/mutations). We use tournament selection for this purpose. Simulation results with the different methods implemented are compared.	1.38 MB	Adobe PDF	Download

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Authors

Bernardino, Anabela M.

Bernardino, Eugénia M.

Sánchez-Pérez, Juan M.

Gómez-Pulido, Juan A.

Vega-Rodríguez, Miguel A.

Moreira Bernardino, Anabela

Bernardino, Eugénia

Abstract(s)

Planning optical communication networks suggests a number of new optimization problems, most of them in the field of combinatorial optimization. We address here the Ring Loading Problem. The objective of the problem is to find a routing scheme such that the maximum weighted load on the ring is minimized. In this paper we consider two variants: (i) demands can be split into two parts, and then each part is sent in a different direction; (ii) each demand must be entirely routed in either of the two directions, clockwise or counterclockwise. In this paper, we propose a genetic algorithm employing multiple crossover and mutation operators. Two sets of available crossover and mutation operators are established initially. In each generation a crossover method is selected for recombination and a mutation method is selected for mutation based on the amount fitness improvements achieve over a number of previous operations (recombinations/mutations). We use tournament selection for this purpose. Simulation results with the different methods implemented are compared.

Description

International Symposium on Distributed Computing and Artificial Intelligence 2008 (DCAI 2008)

Keywords

Optimization Genetic Algorithms Ring Loading Problem

URI

http://hdl.handle.net/10400.8/12819

Citation

Bernardino, A.M., Bernardino, E.M., Sánchez-Pérez, J.M., Gómez-Pulido, J.A., Vega-Rodríguez, M.A. (2009). Solving the Ring Loading Problem Using Genetic Algorithms with Intelligent Multiple Operators. In: Corchado, J.M., Rodríguez, S., Llinas, J., Molina, J.M. (eds) International Symposium on Distributed Computing and Artificial Intelligence 2008 (DCAI 2008). Advances in Soft Computing, vol 50. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-85863-8_28.