Matches in SemOpenAlex for { <https://semopenalex.org/work/W4366987705> ?p ?o ?g. }
- W4366987705 endingPage "8559" @default.
- W4366987705 startingPage "8541" @default.
- W4366987705 abstract "At a time of global epidemic control, the location of the medical logistics distribution center (MLDC) has an important impact on the operation of the entire logistics system to reduce the operating costs of the company, enhance the service quality and effectively control the COVID-19 on the premise of increasing the company’s profits. Thus, the research on the location of MLDC has important theoretical and practical application significance separately. Recently, the TODIM and VIKOR method has been used to solve multiple-attribute group decision-making (MAGDM) issues. The probabilistic uncertain linguistic term sets (PULTSs) are used as a tool for characterizing uncertain information. In this paper, we design the TODIM-VIKOR model to solve the MAGDM in PULT condition. Firstly, some basic concept of PULTSs is reviewed, and TODIM and VIKOR method are introduced. The extended TODIM-VIKOR model is proposed to tackle MAGDM problems under the PULTSs. At last, a numerical case study for medical logistics center site selection (MLCSS) is given to validate the proposed method." @default.
- W4366987705 created "2023-04-27" @default.
- W4366987705 creator A5004772796 @default.
- W4366987705 creator A5011396486 @default.
- W4366987705 creator A5035260283 @default.
- W4366987705 creator A5045133041 @default.
- W4366987705 creator A5051208088 @default.
- W4366987705 creator A5084524299 @default.
- W4366987705 creator A5085550373 @default.
- W4366987705 date "2023-04-25" @default.
- W4366987705 modified "2023-10-08" @default.
- W4366987705 title "TODIM-VIKOR method based on hybrid weighted distance under probabilistic uncertain linguistic information and its application in medical logistics center site selection" @default.
- W4366987705 cites W1974562332 @default.
- W4366987705 cites W1976567794 @default.
- W4366987705 cites W2036559270 @default.
- W4366987705 cites W2053190248 @default.
- W4366987705 cites W2060093109 @default.
- W4366987705 cites W2061083072 @default.
- W4366987705 cites W2067442047 @default.
- W4366987705 cites W2073895815 @default.
- W4366987705 cites W2081606696 @default.
- W4366987705 cites W2117827905 @default.
- W4366987705 cites W2292359941 @default.
- W4366987705 cites W2418380392 @default.
- W4366987705 cites W2474884296 @default.
- W4366987705 cites W2507975617 @default.
- W4366987705 cites W2517211693 @default.
- W4366987705 cites W2527615072 @default.
- W4366987705 cites W2563128797 @default.
- W4366987705 cites W2593995542 @default.
- W4366987705 cites W2658730089 @default.
- W4366987705 cites W2782761971 @default.
- W4366987705 cites W2800926348 @default.
- W4366987705 cites W2801283338 @default.
- W4366987705 cites W2831026053 @default.
- W4366987705 cites W2887147695 @default.
- W4366987705 cites W2901211749 @default.
- W4366987705 cites W2905440559 @default.
- W4366987705 cites W2921341381 @default.
- W4366987705 cites W2924791920 @default.
- W4366987705 cites W2995269853 @default.
- W4366987705 cites W3010333714 @default.
- W4366987705 cites W3011865677 @default.
- W4366987705 cites W3012295806 @default.
- W4366987705 cites W3037379844 @default.
- W4366987705 cites W3044274068 @default.
- W4366987705 cites W3088775364 @default.
- W4366987705 cites W3093935883 @default.
- W4366987705 cites W3113924469 @default.
- W4366987705 cites W3128951492 @default.
- W4366987705 cites W3138543873 @default.
- W4366987705 cites W3155791648 @default.
- W4366987705 cites W3157288788 @default.
- W4366987705 cites W3175373164 @default.
- W4366987705 cites W3179393967 @default.
- W4366987705 cites W3185145551 @default.
- W4366987705 cites W3188894055 @default.
- W4366987705 cites W3188916408 @default.
- W4366987705 cites W3193863295 @default.
- W4366987705 cites W3196079216 @default.
- W4366987705 cites W3198084770 @default.
- W4366987705 cites W3212031517 @default.
- W4366987705 cites W3214983111 @default.
- W4366987705 cites W4200396497 @default.
- W4366987705 cites W4205381090 @default.
- W4366987705 cites W4205799758 @default.
- W4366987705 cites W4206118411 @default.
- W4366987705 cites W4210863744 @default.
- W4366987705 doi "https://doi.org/10.1007/s00500-023-08132-w" @default.
- W4366987705 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/37255921" @default.
- W4366987705 hasPublicationYear "2023" @default.
- W4366987705 type Work @default.
- W4366987705 citedByCount "1" @default.
- W4366987705 countsByYear W43669877052023 @default.
- W4366987705 crossrefType "journal-article" @default.
- W4366987705 hasAuthorship W4366987705A5004772796 @default.
- W4366987705 hasAuthorship W4366987705A5011396486 @default.
- W4366987705 hasAuthorship W4366987705A5035260283 @default.
- W4366987705 hasAuthorship W4366987705A5045133041 @default.
- W4366987705 hasAuthorship W4366987705A5051208088 @default.
- W4366987705 hasAuthorship W4366987705A5084524299 @default.
- W4366987705 hasAuthorship W4366987705A5085550373 @default.
- W4366987705 hasBestOaLocation W43669877051 @default.
- W4366987705 hasConcept C111472728 @default.
- W4366987705 hasConcept C126255220 @default.
- W4366987705 hasConcept C138885662 @default.
- W4366987705 hasConcept C144133560 @default.
- W4366987705 hasConcept C154945302 @default.
- W4366987705 hasConcept C162853370 @default.
- W4366987705 hasConcept C172438850 @default.
- W4366987705 hasConcept C185592680 @default.
- W4366987705 hasConcept C2775924081 @default.
- W4366987705 hasConcept C2779463800 @default.
- W4366987705 hasConcept C2779530757 @default.
- W4366987705 hasConcept C2781463594 @default.
- W4366987705 hasConcept C33923547 @default.
- W4366987705 hasConcept C41008148 @default.
- W4366987705 hasConcept C42475967 @default.