Abstract
Multi-step crossover fusion (MSXF) is a promising crossover method using only the neighborhood structure and the distance measure, when heuristic crossovers are hardly introduced. However, MSXF works unsteadily according to the temperature parameter, like as Simulated Annealing. In this paper, we introduce deterministic multi-step crossover fusion (dMSXF) to take this parameter away. Instead of the probabilistic acceptance of MSXF, neighbors are restricted to be closer to the goal solution, the best candidate of them is selected definitely as the next step solution. The performance of dMSXF is tested on 1max problem and Traveling Salesman Problem, and its superiority to conventional methods, e.g. uniform crossover, is shown.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Sandor Markon, Dirk V. Arnold, Thomas Bäck, Thomas Beielstein, and Hans-Georg Beyer: Thresholding-a Selection Operator for Noisy ES, Congress on Evolutionary Computation, pp. 465–472 (2001)
Nagata, Y. and Kobayashi, S.: Edge Assembly Crossover: A High-power Genetic Algorithm fot the Traveling Salesman Problem, Proceedings of the 7th International Conference on Genetic Algorithms, pp. 450–457 (1997)
Nagata, Y.: Genetic Algorithm for Traveling Salesman Problem using Edge Assembly Crossover: its Proposal and Analysis, Doctoral thesis (2000)
Padberg, M. and G. Rinaldi: A Branch-and-Cut Algorithm for the Resolution of Large-Scale Symmetric Traveling Salesman Problems, SIAM Review, Vol. 33, No. 1 pp. 60–100 (1991)
G. Reinelt, The Traveling Salesman: Computational Solutions for TSP Applications. Vol. 840 of Lecture Notes in Computer Science, Springer-Verlag (1994)
H. Satoh, M. Yamamura, and S. Kobayashi: Minimal Generation Gap Model for GAs Considering Both Exploration and Exploitation, Proc. of IIZUKA, pp. 494–497 (1996)
Gorges-Schleuter, M.: Asparagos96 and the Traveling Salesman Problem, Proc. of the 1997 IEEE International Conference of Evolutionary Computation, pp. 171–174 (1997)
Hisashi Shimodaira: A Diversity Control Oriented Genetic Algorithm (DCGA): Development and Experimental Results, Proceedings of the Genetic and Evolutionary Computation Conference, pp. 603–611 (1999)
Yamada, T. and Ryohei, N.: Scheduling by Generic Local Search with Multi-Step Crossover, Proceedings of the 4th conference on 4th PPSN, pp. 960–969 (1996)
Yamada, T. and Nakano, R.: A GA with multi-step crossover for jobshop scheduling problems, Proc. of Int. Conf. on GAs in Engneering Systems: Innovations and Applications (GALESIA) '95, pp. 146–151 (1995)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2002 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Ikeda, K., Kobayashi, S. (2002). Deterministic Multi-step Crossover Fusion: A Handy Crossover Composition for GAs. In: Guervós, J.J.M., Adamidis, P., Beyer, HG., Schwefel, HP., Fernández-Villacañas, JL. (eds) Parallel Problem Solving from Nature — PPSN VII. PPSN 2002. Lecture Notes in Computer Science, vol 2439. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45712-7_16
Download citation
DOI: https://doi.org/10.1007/3-540-45712-7_16
Published:
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-44139-7
Online ISBN: 978-3-540-45712-1
eBook Packages: Springer Book Archive