Abstract

Low price and good taste of foods are regarded as two major factors for optimal human nutrition. Due to price fluctuations and taste diversity, these two factors cannot be certainly and determinately evaluated. This problem must be viewed from another perspective because of the uncertainty about the amount of nutrients per unit of foods and also diversity of people’s daily needs to receive them.This paper discusses human diet problem in fuzzy environment. The approach deals with multi-objective fuzzy linear programming problem using a fuzzy programming technique for its solution. By prescribing a diet merely based on crisp data, some ofthe realities are neglected. For the same reason, we dealt with human diet problem through fuzzy approach. Results indicated uncertainty about factors of nutrition diet -including taste and price, amount of nutrients and their intake- would affect diet quality, making the proposed diet more realistic.

Highlights

  • In the modern world, people have variant nutrition requirements depending on different positions they have

  • Human Diet Problem was assumed in the form of a fuzzy linear programming with two objective functions

  • This representation is interpreted as membership functions[1]: Optimizing Human Diet Problem Based on Price and Taste

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Summary

Introduction

People have variant nutrition requirements depending on different positions they have. After providing individuals with appropriate foods and a desirable diet, some priorities emerge for selection of optimal nutrition regime for them Examples of these priorities are taste and final cost of the eaten food. Using Bellman and Zadeh’s fuzzy decision-making process, the MOFLPP is converted into an equivalent crisp LPP Converting the problem into an equivalent crisp non-linear programming problem, it is solved by fuzzy decisive set method. Human Diet Problem was assumed in the form of a fuzzy linear programming with two objective functions. In the respective nutrition model which is in the form of a multi-objective fuzzy linear program, good results were achieved for presenting an optimum diet through minimizing final cost and maximizing the taste felt in each meal

Preliminaries
Algorithm
Numerical example 1
Application in Human Diet Problem
Conclusions
Findings
2: United States Department of Agriculture

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