This paper proposes an optimization algorithm based on how human fight andlearn from each duelist. Since this algorithm is based on population, theproposed algorithm starts with an initial set of duelists. The duel is todetermine the winner and loser. The loser learns from the winner, while thewinner try their new skill or technique that may improve their fightingcapabilities. A few duelists with highest fighting capabilities are called aschampion. The champion train a new duelists such as their capabilities. The newduelist will join the tournament as a representative of each champion. Allduelist are re-evaluated, and the duelists with worst fighting capabilities iseliminated to maintain the amount of duelists. Two optimization problem isapplied for the proposed algorithm, together with genetic algorithm, particleswarm optimization and imperialist competitive algorithm. The results show thatthe proposed algorithm is able to find the better global optimum and fasteriteration.
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