Solving Tea Blending Problems Using Interactive Fuzzy Multi-Objective Linear Programming

Blending is a classical and well-known optimization problem that has been applied in the food, steel, and composite material industries. However, tea blending is more complicated than general problems due to the variety of products, processes, and sources of raw materials and semi-products. So, in t...

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Vydáno v:Processes Ročník 11; číslo 1; s. 49
Hlavní autoři: Jarernsuk, Saran, Phruksaphanrat, Busaba
Médium: Journal Article
Jazyk:angličtina
Vydáno: Basel MDPI AG 01.01.2023
Témata:
Algorithms
Blending
Case studies
Composite materials
Costs
Enzymes
Food composition
Linear programming
Mathematical models
Mathematical programming
Monte Carlo simulation
Multiple objective analysis
Objectives
Optimization
Outsourcing
Polyphenols
Production costs
Production planning
Raw materials
Tea
Thailand
ISSN:2227-9717, 2227-9717
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Shrnutí:Blending is a classical and well-known optimization problem that has been applied in the food, steel, and composite material industries. However, tea blending is more complicated than general problems due to the variety of products, processes, and sources of raw materials and semi-products. So, in this research, a fuzzy multi-objective model for the tea blending problem was proposed to minimize the total production cost and the deviation of quality target score; it provides a more robust and flexible method than existing models for complex real-world problems. Existing research works of a blending problem consider only raw material cost, but semi-product cost and processing cost are included in the proposed model that matches the actual case. Losses that occur during production are also incorporated. The selection of appropriate raw materials and semi-product sources can be obtained with the preferred levels of cost and quality by the proposed algorithm. The interactive fuzzy multi-objective programming to solve the problem has advantages over existing interactive programming methods. It is easy to manipulate interactively to obtain more efficient solutions than existing methods and both balanced and unbalanced solutions can be selected. The comparison of the results of an existing approach and the interactive fuzzy multi-objective programming algorithm for the tea industry is illustrated.
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ISSN:2227-9717
2227-9717
DOI:10.3390/pr11010049