Gül Tekin Temur
Orcid: 0000-0003-3853-0974
According to our database1,
Gül Tekin Temur
authored at least 19 papers
between 2014 and 2023.
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Bibliography
2023
A Unified Multiplicative Group Best-Worst Method with a New Assessment Approach for Dissimilar Markets.
Informatica, 2023
2022
J. Intell. Fuzzy Syst., 2022
J. Intell. Fuzzy Syst., 2022
2021
A Robust Multi-Critia Decision-Making Procedure for Outsourcing Decisions in Reverse Logistics.
Int. J. Oper. Res. Inf. Syst., 2021
An Integrated Fuzzy Multi-Criteria Approach for E-Waste Collection Center Location Problem.
Int. J. Fuzzy Syst. Appl., 2021
2020
A spherical fuzzy analytic hierarchy process based approach to prioritize career management activities improving employee retention.
J. Intell. Fuzzy Syst., 2020
Evaluation of positive employee experience using hesitant fuzzy analytic hierarchy process.
J. Intell. Fuzzy Syst., 2020
Wind turbine evaluation using the hesitant fuzzy AHP-TOPSIS method with a case in Turkey.
J. Intell. Fuzzy Syst., 2020
2019
Early Warning System Design for WEEE Reverse Logistic Network: A Case Study in Turkey.
Int. J. Knowl. Based Organ., 2019
2018
A robust MCDM approach for ERP system selection under uncertain environment based on worst case scenario.
J. Enterp. Inf. Manag., 2018
CNC router selection for SMEs in woodwork manufacturing using hesitant fuzzy AHP method.
J. Enterp. Inf. Manag., 2018
2017
Int. J. Inf. Technol. Proj. Manag., 2017
A Novel Approach for Multi-Period Reverse Logistics Network Design under High Uncertainty.
Int. J. Comput. Intell. Syst., 2017
Energy-related CO2 emission forecast for Turkey and Europe and Eurasia: A discrete grey model approach.
Grey Syst. Theory Appl., 2017
2016
A novel multi attribute decision making approach for location decision under high uncertainty.
Appl. Soft Comput., 2016
2014
Facility Location Selection in Reverse Logistics Using a Type-2 Fuzzy Decision Aid Method.
Proceedings of the Supply Chain Management Under Fuzziness, 2014
An Axiomatic Design Approach to the Classification of Reverse Logistics Network Design Studies Under Fuzziness.
Proceedings of the Supply Chain Management Under Fuzziness, 2014
A fuzzy expert system design for forecasting return quantity in reverse logistics network.
J. Enterp. Inf. Manag., 2014