Standardising fresh produce selection and grading process for improving quality assurance in perishable food supply chains: an integrated Fuzzy AHP-TOPSIS framework

ABSTRACT

Food retailer’s grading and selection is an essential process for determining the consumer priceand guaranteeing the quality before launching to the market. Such a grading process, however, often relies on human expertise for making a subjective judgement. This paper proposes a hybrid approach using fuzzy analytic hierarchy process for determining weights of evaluation criteria and TOPSIS (Technique for Order Preference by Similarity to an Ideal Solution) for ranking different batches of produce, which facilitates the initial sorting and grading process for procurement. A case study is conducted and results are compared with existing methods, demonstrating the merit of the approach in generating reliable results without heavy technology investment.

KEYWORDS:

• Fuzzy AHP
• TOPSIS
• Multiple Criteria Decision-Making (MCDM)
• food quality management
• decision support in food industry

Disclosure statement

No potential conflict of interest was reported by the authors.

Correction Statement

This article has been republished with minor changes. These changes do not impact the academic content of the article.

Additional information

Funding

This research is supported by the National Natural Science Foundation of China under [Grant 71801154]; and Science Foundation for Youth Scholars of Shenzhen University under [Grant 2019070 and 189692].