Abstract
Interactive Evolutionary Computational (IEC) algorithms have to be able to search robustly under the conditions of lower population number and fewer generations. This paper presents a novel IEC called interactive Ant System (iAS) which is interactively used by an user to determine the optimized combination of jacket, T-shirt, trousers and shoes. The iAS is the first of its kind in extending the well-known ACO to interactive optimization. Our experiments show that the iAS is capable of optimizing the user’s requests in real time.
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Tanabe, R., Gonsalves, T., Itoh, K. (2012). Interactive ACO Algorithm toward Practical IEC Application Fields. In: Kim, JH., Lee, K., Tanaka, S., Park, SH. (eds) Advanced Methods, Techniques, and Applications in Modeling and Simulation. Proceedings in Information and Communications Technology, vol 4. Springer, Tokyo. https://doi.org/10.1007/978-4-431-54216-2_34
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DOI: https://doi.org/10.1007/978-4-431-54216-2_34
Publisher Name: Springer, Tokyo
Print ISBN: 978-4-431-54215-5
Online ISBN: 978-4-431-54216-2
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