Sensory Laboratory, Institute of Food Technology, Szent István University, Villányi út 29-43., 1118 Budapest, Hungary.
Plasma Chemistry Research Group, Research Centre for Natural Sciences, H-1117 Budapest, Magyar tudósok krt. 2, Hungary.
Food Chem. 2021 May 15;344:128617. doi: 10.1016/j.foodchem.2020.128617. Epub 2020 Nov 12.
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.
寻找最优解决方案通常需要多准则优化。排名差异总和（SRD）算法可以有效地解决此类问题。本文将讨论其原理和早期应用，并对发表在食品科学各个子领域的论文进行荟萃分析，例如食品化学分析、食品工程、食品技术、食品微生物学、质量控制和感官分析。精心挑选的实际案例研究概述了使用免费、易于使用和经过验证的方法进行多准则优化的广泛应用。结果以有助于科学家和从业者（他们对多准则优化不太熟悉）将该方法集成到他们的研究项目中的方式呈现和讨论。SRD 的实用性（可选地与 ANOVA 等其他统计方法结合使用）在总共 12 个案例研究中得到了证明，涵盖了来自食品科学各个子领域的各种方法比较和数据评估场景。
