Research Article
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Year 2020, Volume: 6 Issue: 1, 7 - 12, 31.03.2020

Billur Ecer Ahmet Aktas Mehmet Kabak Metin Dağdeviren

https://doi.org/10.22399/ijcesen.646157
Cited By: 3

Abstract

References

  • [1] Kabak Mehmet, Sağlam Fatih, Aktaş Ahmet, “Usability analysis of different distance measures on TOPSIS” Journal of the Faculty of Engineering and Architecture of Gazi University, 32, 35-43 (2017)
  • [2] T. L. Saaty, The Analytic Hierarchy Process, McGraw-Hill, New York 1980
  • [3] Dağdeviren, Metin “Personnel selection with Fuzzy Analytical Hierarchy Process and an application” Journal of the Faculty of Engineering and Architecture of Gazi University, 22, 791-799 (2007)
  • [4] Wang, J., M. Li, Y. Liu, H. Zhang, W. Zou, L. Cheng. “Safety assessment of shipping routes in the South China Sea based on the fuzzy analytic hierarchy process” Safety Science, 62, 46–57 (2014)
  • [5] Calabrese, A., R. Costa, T. Menichini. “Using Fuzzy AHP to manage Intellectual Capital assets: An application to the ICT service industry” Expert Systems with Applications, 40, 3747–3755 (2013)
  • [6] García, J.L., A. Alvarado, J. Blanco, E. Jiménez, A.A. Maldonado, G. Cortés, “Multi-attribute evaluation and selection of sites for agricultural product warehouses based on an Analytic Hierarchy Process” Computers and Electronics in Agriculture, 100, 60–69 (2014)
  • [7] Caputo, A. C., P. M. Pelagagge, P. Salini. “AHP-based methodology for selecting safety devices of industrial machinery” Safety Science, 53, 202–218 (2013)
  • [8] Oztaysi, B. “A decision model for information technology selection using AHP integrated TOPSIS-Grey: The case of content management systems” Knowledge-Based Systems, 70, 44–54 (2014)
  • [9] Ishizaka, A., N. H. Nguyen. “Calibrated fuzzy AHP for current bank account selection”, Expert Systems with Applications, 40, 3775–3783 (2013)
  • [10] Junior, F. R. L., L. Osiro, L. C. R. Carpinetti. “A comparison between Fuzzy AHP and Fuzzy TOPSIS methods to supplier selection” Applied Soft Computing, 21, 194–209 (2014)
  • [11] Efe, B. “An integrated fuzzy multi criteria group decision making approach for ERP system selection” Applied Soft Computing, 38, 106–117 (2016)
  • [12] Zadeh, L.A. “Fuzzy Sets” Information and Control, 8, 338 – 353 (1965)
  • [13] Rouyendegh, B. D., T. E. Erkan. “Selection of Academic Staff Using The Fuzzy Analytic Hierarchy Process (FAHP): A Pilot Study” Technical Gazette, 19, 923-929 (2012)
  • [14] Ansari, S. R., P. K. Mittal, R. Chandna. “Multi-criteria decision making using fuzzy logic approach for evaluating the manufacturing flexibility” Journal of Engineering and Technology Research, 2, 237-244 (2010)

Determining the Best Maternity Hospital by Using a Fuzzy Decision Making Model

Year 2020, Volume: 6 Issue: 1, 7 - 12, 31.03.2020

Billur Ecer Ahmet Aktas Mehmet Kabak Metin Dağdeviren

https://doi.org/10.22399/ijcesen.646157
Cited By: 3

Abstract

Despite having child brings great responsibility, people want to have a child instinctively. In the context of childcare, parental responsibility requires that children should be born in good conditions and grow healthy and happily. Parents’ first responsibility is to ensure that children born in a healthy way. Nowadays, pregnant women visit doctor regularly and monitor the infant development. There are too many doctors and hospitals working in obstetrics area.  The increasing number of alternatives and selection criteria makes it difficult to find a compromise solution in terms of conflicting selection criteria. Therefore, using analytical methods becomes necessary while making the decision of hospital choice for pregnancy follow-up. The main aim of this study is to develop a decision tool for determining the best hospital for pregnancy process. Because of the existence of linguistic evaluations in the decision process, Fuzzy Analytic Hierarchy Process is used in this study for determining the best alternative. An application of a real world problem is presented to demonstrate the applicability of the proposed methodology. Within the presented application weight of hospital selection criteria and priority values of five predetermined alternative hospitals in Ankara are calculated are determined. The obtained results of the study shows that staff quality and technical conditions are the most important criteria for hospital selection.

Keywords

Multiple Criteria Decision Making Analytic Hierarchy Process Triangular Fuzzy Sets Healthcare Management

References

  • [1] Kabak Mehmet, Sağlam Fatih, Aktaş Ahmet, “Usability analysis of different distance measures on TOPSIS” Journal of the Faculty of Engineering and Architecture of Gazi University, 32, 35-43 (2017)
  • [2] T. L. Saaty, The Analytic Hierarchy Process, McGraw-Hill, New York 1980
  • [3] Dağdeviren, Metin “Personnel selection with Fuzzy Analytical Hierarchy Process and an application” Journal of the Faculty of Engineering and Architecture of Gazi University, 22, 791-799 (2007)
  • [4] Wang, J., M. Li, Y. Liu, H. Zhang, W. Zou, L. Cheng. “Safety assessment of shipping routes in the South China Sea based on the fuzzy analytic hierarchy process” Safety Science, 62, 46–57 (2014)
  • [5] Calabrese, A., R. Costa, T. Menichini. “Using Fuzzy AHP to manage Intellectual Capital assets: An application to the ICT service industry” Expert Systems with Applications, 40, 3747–3755 (2013)
  • [6] García, J.L., A. Alvarado, J. Blanco, E. Jiménez, A.A. Maldonado, G. Cortés, “Multi-attribute evaluation and selection of sites for agricultural product warehouses based on an Analytic Hierarchy Process” Computers and Electronics in Agriculture, 100, 60–69 (2014)
  • [7] Caputo, A. C., P. M. Pelagagge, P. Salini. “AHP-based methodology for selecting safety devices of industrial machinery” Safety Science, 53, 202–218 (2013)
  • [8] Oztaysi, B. “A decision model for information technology selection using AHP integrated TOPSIS-Grey: The case of content management systems” Knowledge-Based Systems, 70, 44–54 (2014)
  • [9] Ishizaka, A., N. H. Nguyen. “Calibrated fuzzy AHP for current bank account selection”, Expert Systems with Applications, 40, 3775–3783 (2013)
  • [10] Junior, F. R. L., L. Osiro, L. C. R. Carpinetti. “A comparison between Fuzzy AHP and Fuzzy TOPSIS methods to supplier selection” Applied Soft Computing, 21, 194–209 (2014)
  • [11] Efe, B. “An integrated fuzzy multi criteria group decision making approach for ERP system selection” Applied Soft Computing, 38, 106–117 (2016)
  • [12] Zadeh, L.A. “Fuzzy Sets” Information and Control, 8, 338 – 353 (1965)
  • [13] Rouyendegh, B. D., T. E. Erkan. “Selection of Academic Staff Using The Fuzzy Analytic Hierarchy Process (FAHP): A Pilot Study” Technical Gazette, 19, 923-929 (2012)
  • [14] Ansari, S. R., P. K. Mittal, R. Chandna. “Multi-criteria decision making using fuzzy logic approach for evaluating the manufacturing flexibility” Journal of Engineering and Technology Research, 2, 237-244 (2010)
There are 14 citations in total.

Details

Primary Language English
Subjects Engineering
Journal Section Research Articles
Authors

Billur Ecer 0000-0001-9692-1450

Ahmet Aktas 0000-0002-4394-121X

Mehmet Kabak 0000-0002-8576-5349

Metin Dağdeviren 0000-0003-2121-5978

Publication Date March 31, 2020
Submission Date November 13, 2019
Acceptance Date February 12, 2020
Published in Issue Year 2020 Volume: 6 Issue: 1

Cite

APA Ecer, B., Aktas, A., Kabak, M., Dağdeviren, M. (2020). Determining the Best Maternity Hospital by Using a Fuzzy Decision Making Model. International Journal of Computational and Experimental Science and Engineering, 6(1), 7-12. https://doi.org/10.22399/ijcesen.646157

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