Abstract
This paper proposes an optimization algorithm based on human fight and learn from each duelist. The proposed algorithm starts with an initial set of duelists. The duel is to determine the winner and loser. The loser learns from the winner, while the winner try their new skill or technique that may improve their fighting capabilities. A few duelists with highest fighting capabilities are called as champion. The champion train a new duelist such as their capabilities. The new duelist will join the tournament as a representative of each champion. All duelist are re-evaluated, and the duelists with worst fighting capabilities is eliminated to maintain the amount of duelists. Several benchmark functions is used in this work. The results shows that Duelist Algorithm outperform other algorithms in several functions.
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Biyanto, T.R. et al. (2016). Duelist Algorithm: An Algorithm Inspired by How Duelist Improve Their Capabilities in a Duel. In: Tan, Y., Shi, Y., Niu, B. (eds) Advances in Swarm Intelligence. ICSI 2016. Lecture Notes in Computer Science(), vol 9712. Springer, Cham. https://doi.org/10.1007/978-3-319-41000-5_4
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DOI: https://doi.org/10.1007/978-3-319-41000-5_4
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