Simulaci\'on de la distribuci\'on de alimento en el cultivo de camar\'on

TL;DR

This paper simulates food distribution strategies in shrimp farming, using genetic algorithms and fuzzy logic to optimize growth conditions, resulting in a significant reduction in culture time from 22 to 14 weeks.

Contribution

It introduces a simulation model that integrates genetic algorithms and fuzzy logic to optimize food distribution in shrimp cultivation, improving efficiency.

Findings

Simulation closely matches real-world data.

Optimized distribution reduces culture time by 8 weeks.

Fuzzy logic effectively evaluates environmental parameters.

Abstract

This document presents the experimentation of 4 cases of food distribution for shrimp farming. The distributions are based on the location of the automatic feeders. Three cases applied in reality and a fourth case where the food is irrigated on the crop simultaneously and uniformly. In a first stage, the simulation of the three distribution cases is successfully adjusted to reality, where the trend of the shrimp growth curve is correlated with the historical data curve. A second stage where you experiment in 16 configurations that are based on the amount of food, the density of biomass and the distribution of the food. The simulation adopts the concepts of genetic algorithms to improve the population and fuzzy logic as an agent evaluation technique for decision-making against the quality of physical-chemical parameters in the simulated environment. The results of these interactions reveal a reduction in the simulated total culture time from 22 weeks to 14 weeks.