Mohd Faizal Omar, J. Shukor, Maznah Mat Kassim, Kasmaruddin Che Hussin
{"title":"Decision model using hierarchical fuzzy TOPSIS: Towards improving decision making in food waste management","authors":"Mohd Faizal Omar, J. Shukor, Maznah Mat Kassim, Kasmaruddin Che Hussin","doi":"10.52462/jlls.119","DOIUrl":null,"url":null,"abstract":"Technique for Order Performance by Similarity to Ideal Solution (TOPSIS) is based on decision model to measure alternative with shortest distance to positive ideal solution and the farthest distance from negative ideal solution. With growing complexity in decision making, vagueness and uncertainty often exist in human judgement. To manage conflicting criteria, a hierarchy structure in TOPSIS is proposed where the main criteria, sub-criteria, and alternatives are arranged in multi-level. To rate each alternatives, the weight of each criterion is evaluated using linguistic value before converted into fuzzy number as a way to measure the experts opinion. In this paper, we demonstrates our general framework for the development of hierarchal fuzzy TOPSIS. We also highlighted our initial finding on the criteria and alternatives in our case study i.e. selection of decomposition technology for food waste management. It is anticipates our work will contributes better decision making in the related area.","PeriodicalId":16272,"journal":{"name":"Journal of Language and Linguistic Studies","volume":" ","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2021-09-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Language and Linguistic Studies","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.52462/jlls.119","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
Abstract
Technique for Order Performance by Similarity to Ideal Solution (TOPSIS) is based on decision model to measure alternative with shortest distance to positive ideal solution and the farthest distance from negative ideal solution. With growing complexity in decision making, vagueness and uncertainty often exist in human judgement. To manage conflicting criteria, a hierarchy structure in TOPSIS is proposed where the main criteria, sub-criteria, and alternatives are arranged in multi-level. To rate each alternatives, the weight of each criterion is evaluated using linguistic value before converted into fuzzy number as a way to measure the experts opinion. In this paper, we demonstrates our general framework for the development of hierarchal fuzzy TOPSIS. We also highlighted our initial finding on the criteria and alternatives in our case study i.e. selection of decomposition technology for food waste management. It is anticipates our work will contributes better decision making in the related area.
TOPSIS (Order Performance by Similarity by Ideal Solution)是一种基于决策模型来度量与正理想解距离最短和与负理想解距离最远的方案。随着决策的日益复杂,人类的判断往往存在模糊性和不确定性。为了管理相互冲突的标准,在TOPSIS中提出了一种层次结构,将主标准、子标准和备选标准分层排列。为了对每个备选方案进行评级,首先使用语言值来评估每个标准的权重,然后将其转换为模糊数来衡量专家的意见。在本文中,我们展示了我们开发层次模糊TOPSIS的一般框架。我们还强调了我们在案例研究中对标准和替代方案的初步发现,即选择用于食物垃圾管理的分解技术。预计我们的工作将有助于相关领域更好的决策。