4.7 Article

Multicriteria decision making for evergreen problems in food science by sum of ranking differences

期刊

FOOD CHEMISTRY
卷 344, 期 -, 页码 -

出版社

ELSEVIER SCI LTD
DOI: 10.1016/j.foodchem.2020.128617

关键词

Pareto optimization; Food quality; Multiobjective decision making; Food engineering; Food microbiology; Quality control; Sensory evaluation

资金

  1. National Research, Development and Innovation Office of Hungary (OTKA) [K119269, K134260]
  2. European Union
  3. European Social Fund [EFOP-3.6.3-VEKOP-16-2017-00005]
  4. Premium Postdoctoral Researcher Program of Hungarian Academy of Sciences
  5. Janos Bolyai Research Scholarship of the Hungarian Academy of Sciences
  6. National Research, Development and Innovation Office of Hungary [PD 134416]

向作者/读者索取更多资源

This paper discusses the application and advantages of the sum of ranking differences (SRD) algorithm in multicriteria optimization, showcasing its wide range of applications through carefully selected case studies and providing guidance for scientists and practitioners unfamiliar with multicriteria optimization on how to integrate the method into their research projects.
Finding optimal solutions usually requires multicriteria optimization. The sum of ranking differences (SRD) algorithm can efficiently solve such problems. Its principles and earlier applications will be discussed here, along with meta-analyses of papers published in various subfields of food science, such as analytics in food chemistry, food engineering, food technology, food microbiology, quality control, and sensory analysis. Carefully selected real case studies give an overview of the wide range of applications for multicriteria optimizations, using a free, easy-to-use and validated method. Results are presented and discussed in a way that helps scientists and practitioners, who are less familiar with multicriteria optimization, to integrate the method into their research projects. The utility of SRD, optionally coupled with other statistical methods such as ANOVA, is demonstrated on altogether twelve case studies, covering diverse method comparison and data evaluation scenarios from various subfields of food science.

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