Fuzzy multi-criteria decision-making procedure for evaluating advanced manufacturing system investments
By E. Karsak, E. Tolga. 2001
309 citations recorded by the source corpus.
Subfields: Management Information Systems, Management Science and Operations Research, Strategy and Management
View Paper: https://www.semanticscholar.org/paper/c45ce6ce349de97ce786fdcdd9b16b6b4877d7e8
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Management Information Systems
- G. Parvathinathan
- Felix Tung Sun Chan
- Orlando Durán
- Ni-Bin Chang
- Avinash Samvedi
- Metin Dagdeviren
- Vipul Jain
- Ihsan Yüksel
In Management Science and Operations Research
- Metin Dagdeviren
- Ihsan Yüksel
- Ni-Bin Chang
- Vipul Jain
- Avinash Samvedi
- G. Parvathinathan
- Felix Tung Sun Chan
- Orlando Durán
In Strategy and Management
- Metin Dagdeviren
- Ihsan Yüksel
- Vipul Jain
- Avinash Samvedi
- G. Parvathinathan
- Felix Tung Sun Chan
- Orlando Durán
- R. Venkata Rao
Citations in the corpus
- Computer-aided machine-tool selection based on a Fuzzy-AHP approach (2008, methodology): “According Karsak and Tolga (2001), DCF methods appear as the most popular economic justification methodology; however, determining cash flows (revenues, expenses) and discount rates as crisp values can lead to erroneous results in most real-life applications. The results of the surveys conducted by ”
- Flexible manufacturing system selection using a combinatorial mathematics-based decision-making method (2009, background): “Karsak and Tolga ( 2001 ) proposed a fuzzy decision algorithm to select the most suitable advanced manufacturing system alternative.”
- Developing a fuzzy analytic hierarchy process (AHP) model for behavior-based safety management (2008, methodology): “In practical applications, the triangular form of the membership function is used most often for representing fuzzy numbers [13,24,27,49].”
- Combining GIS with fuzzy multicriteria decision-making for landfill siting in a fast-growing urban region. (2008, methodology): “Therefore, the integration of fuzzy set and AHP gives a much better and more exact representation of relationship between criteria and alternatives (Lee et al., 1998; Chiadamrong, 1999; Yu and Skibniewski, 1999; Choi and Oh, 2000; Karsak and Tolga, 2001).”
- Quantifying risks in a supply chain through integration of fuzzy AHP and fuzzy TOPSIS (2013, methodology): “They have the benefit of combining approaches like fuzzy theory, which by its very nature is built to handle subjective assessments, with analytical tools such as AHP, which is a proven tool for handling multi criteria decision making (MCDM) problems (Karsak and Tolga 2001, Zayed et al. 2008).”