Abstract. The optimization problems on real-world usually have nonlinear characteristics. Solving non-linear problems is time-consuming.

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Mixing broiler chicken and layer hens feed using various feed ingredients is a difficult task. The feed must fulfill the minimum nutrient requirement and must break the constraint. Some classic approach like Pearson's Square has been already introduced to solve this problem. However, the approaches cannot guarantee to fulfill nutrient requirements and desirable price. The two metaheuristic algorithms Evolution Strategies (ES) and Firefly Algorithms (FA) are being proposed in this paper to know how well they performed this problems. Result show that ES is perform much better compared to classic Pearson's Square, but ES itself is outperform by FA on both cases.

Abstract.Rainfall is very influential in our daily lives, ranging from agriculture, aviation, to flood-prone areas. The intensity of rainfall is used as an early detection for preventing harmful effects of rainfall. This research used Sugeno Fuzzy Logic, where the prediction is accomplished by mapping rules from the data obtained using the K-Means Clustering Algorithm as the classification to form the membership function and mapping rules and Firefly Alghorithm for optimization output. The test result from the 30 examined data found is 2.93 RMSE. This shows that the data support from K-Means Clustering and Firefly Algorithms of the fuzzy logic can predict precipitation accurately.