Extension of the TOPSIS method for decision-making problems with fuzzy data

By Gholam Reza Jahanshahloo, F. Lotfi, Mohammad Izadikhah. Applied Mathematics and Computation, 2006

654 citations recorded by the source corpus.

Subfields: Control and Systems Engineering, Management Science and Operations Research, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/7348b3a5debd442f216acf456a505de471ecbac4

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Control and Systems Engineering

1. Suresh Kumar Goyal
2. Zlatko Pavić
3. Anjali Awasthi
4. Young Chel Kwun
5. J. H. Park
6. Il Young Park
7. Tabasam Rashid
8. Satyaveer Singh Chauhan

In Management Science and Operations Research

1. Young Chel Kwun
2. J. H. Park
3. Il Young Park
4. Xuegong Tan
5. Suresh Kumar Goyal
6. Zlatko Pavić
7. Anjali Awasthi
8. Tabasam Rashid

In Statistics and Probability

1. Young Chel Kwun
2. J. H. Park
3. Il Young Park
4. Xuegong Tan
5. Suresh Kumar Goyal
6. Zlatko Pavić
7. Anjali Awasthi
8. Tabasam Rashid

Citations in the corpus

• A multi-criteria decision making approach for location planning for urban distribution centers under uncertainty (2011, methodology): “Fuzzy TOPSIS has been applied to facility location problems by researchers in [23,28–31].”
• Notes on TOPSIS method (2013, methodology): “In the case of TOPSIS method the first generalization refers to the processing of insufficiently precise data, namely, fuzzy data (see [6], [5], [1]).”
• TOPSIS for Hesitant Fuzzy Linguistic Term Sets (2013, methodology): “25,26,29–36 The TOPSIS method is extended for triangular fuzzy numbers in Refs.”
• Evaluation of hazardous waste transportation firms by using a two step fuzzy-AHP and TOPSIS methodology (2009, methodology): “The procedure of TOPSIS can be expressed in a series of steps (Jahanshahloo et al., 2006; Olson, 2004; Sen & Yang, 1998; Yang & Hung, 2007):”
• Fuzzy Group Decision Making for the Selection of Facility Location (2011, methodology): “Jahanshahloo et al. (2006) extended the TOPSIS method to decision-making problems with fuzzy data and they used the concept of α-cuts to normalize fuzzy numbers.”
• Extension of the TOPSIS method for decision making problems under interval-valued intuitionistic fuzzy environment (2011, background): “Thus, many researchers [6–12] extended TOPSIS approach to fuzzy environment as a natural generalization of TOPSIS models.”
• The interval-valued fuzzy TOPSIS method and experimental analysis (2008, positive): “Thus, an extension of TOPSIS to the fuzzy environment is a natural generalization of TOPSIS models [6,11,17].”