Hybrid firefly genetic algorithm and integral fuzzy quadratic programming to an optimal Moroccan diet

K. E. El Moutaouakil, A. Ahourag, S. Chakir, Z. Kabbaj, S. Chellack, M. Cheggour, H. Baizri
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引用次数: 3

Abstract

In this paper, we solve the Moroccan daily diet problem based on 6 optimization programming (P) taking into account dietary guidelines of US department of health, human services, and department of agriculture. The objective function controls the fuzzy glycemic load, the favorable nutrients gap, and unfavorable nutrient excess. To transform the proposed program into a line equation, we use the integral fuzzy ranking function. To solve the obtained model, we use the Hybrid Firefly Genetic Algorithm (HFGA) that combines some advantages of the Firefly Algorithm (FA) and the Genetic Algorithm (GA). The proposed model produces the best and generic diets with reasonable glycemic loads and acceptable core nutrient deficiencies. In addition, the proposed model showed remarkable consistency with the uniform distribution of glycemic load of different foods.
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混合萤火虫遗传算法和积分模糊二次规划的最佳摩洛哥饮食
本文结合美国卫生部、人类服务部和农业部的膳食指南,基于6优化规划(P)解决了摩洛哥人的日常饮食问题。目标函数控制模糊血糖负荷、有利营养缺口和不利营养过剩。为了将所提出的规划转化为直线方程,我们使用了积分模糊排序函数。为了求解得到的模型,我们使用混合萤火虫遗传算法(HFGA),它结合了萤火虫算法(FA)和遗传算法(GA)的一些优点。该模型产生的最佳通用日粮具有合理的血糖负荷和可接受的核心营养缺乏症。此外,所提出的模型与不同食物的血糖负荷均匀分布具有显著的一致性。
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来源期刊
Mathematical Modeling and Computing
Mathematical Modeling and Computing Computer Science-Computational Theory and Mathematics
CiteScore
1.60
自引率
0.00%
发文量
54
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