SECOND HAND CAR PURCHASING PROBLEM VIA AN INTEGRATED MULTI-CRITERIA DECISION MAKING SOFTWARE
DOI:
https://doi.org/10.20319/mijst.2017.s31.159177Keywords:
FAHP, TOPSIS, MAUT, Entropy, Multi Criteria Decision MakingAbstract
Automotive industry shows a growing trend in recent years. Both new car and used car market is one of the leading sectors in many countries. In recent years, people prefer to purchase used or second-hand cars rather than new cars. Therefore, it is important to make right decision while purchasing second hand car. Consequently, second hand car purchasing problem (SHCPP) is an up-to-date multi criteria decision problem (MCDMP) almost throughout the world. A software is developed by using C# programming language and this software is usedto solve SHCPP problem. By using Entropy or Fuzzy Analytic Hierarchy Process (FAHP) methods weights of criteria of MCDM problems are calculated by using the developed software. Later this software can be used to determine the optimum alternative using Multi-Attribute Utility Theory (MAUT) or Technique for Order Performance by Similarity to Ideal Solution (TOPSIS) which can be selected by user. Software has the flexibility to solve many different problems and has the diversity to select both methods of calculating weights of criteria and solution methods by user.
References
Abidin, M. Z., Rusli, R., & Shariff, A. M. (2016). Technique for Order Performance by Similarity to Ideal Solution (TOPSIS)-Entropy Methodology for Inherent Safety Design Decision Making Tool. Procedia Engineering, 148, 1043–1050. https://doi.org/10.1016/j.proeng.2016.06.587
Ananda, J., & Herath, G. (2005). Evaluating public risk preferences in forest land-use choices using multi-attribute utility theory. Ecological Economics, 55(3), 408–419. https://doi.org/10.1016/j.ecolecon.2004.12.015
Asilkan, O., & Irmak, S. (2009). Ikinci el otomobillerin gelecekteki fiyatlarinin yapay sinir aglari ile tahmin edilmesi. Süleyman Demirel Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi, 14(2). Retrieved from http://dergipark.ulakbim.gov.tr/sduiibfd/article/download/5000122484/5000112789
Babashamsi, P., Golzadfar, A., Yusoff, N. I. M., Ceylan, H., & Nor, N. G. M. (2016). Integrated fuzzy analytic hierarchy process and VIKOR method in the prioritization of pavement maintenance activities. International Journal of Pavement Research and Technology, 9(2), 112–120. https://doi.org/10.1016/j.ijprt.2016.03.002
Baky, I. A. (2014). Interactive TOPSIS algorithms for solving multi-level non-linear multi-objective decision-making problems. Applied Mathematical Modelling, 38(4), 1417–1433. https://doi.org/10.1016/j.apm.2013.08.016
Baykasoglu, A., & Golcuk, I. (2015). Development of a novel multiple-attribute decision making model via fuzzy cognitive maps and hierarchical fuzzy TOPSIS. Information Sciences, 301, 75–98. https://doi.org/10.1016/j.ins.2014.12.048
Biju, P. L., Shalij, P. R., & Prabhushankar, G. V. (2015). Evaluation of customer requirements and sustainability requirements through the application of fuzzy analytic hierarchy process. Journal of Cleaner Production, 108, Part A, 808–817. https://doi.org/10.1016/j.jclepro.2015.08.051
Canbolat, Y. B., Chelst, K., & Garg, N. (2007). Combining decision tree and MAUT for selecting a country for a global manufacturing facility. Omega, 35(3), 312–325. https://doi.org/10.1016/j.omega.2005.07.002
Chang, D.-Y. (1996). Applications of the extent analysis method on fuzzy AHP. European Journal of Operational Research, 95(3), 649–655. https://doi.org/10.1016/0377-2217(95)00300-2
Ertugrul, I., & Oztas, T. (2014). Business Mobile-line Selection in Turkey by Using Fuzzy TOPSIS, One of the Multi-criteria Decision Methods. Procedia Computer Science, 31, 40–47. https://doi.org/10.1016/j.procs.2014.05.243
Gim, B., & Kim, J. W. (2014). Multi-criteria evaluation of hydrogen storage systems for automobiles in Korea using the fuzzy analytic hierarchy process. International Journal of Hydrogen Energy, 39(15), 7852–7858. https://doi.org/10.1016/j.ijhydene.2014.03.066
Gómez-Limón, J. A., Arriaza, M., & Riesgo, L. (2003). An MCDM analysis of agricultural risk aversion. European Journal of Operational Research, 151(3), 569–585. https://doi.org/10.1016/S0377-2217(02)00625-2
Guo, S., & Zhao, H. (2015). Optimal site selection of electric vehicle charging station by using fuzzy TOPSIS based on sustainability perspective. Applied Energy, 158, 390–402. https://doi.org/10.1016/j.apenergy.2015.08.082
Ho, W. (2008). Integrated analytic hierarchy process and its applications – A literature review. European Journal of Operational Research, 186(1), 211–228. https://doi.org/10.1016/j.ejor.2007.01.004
Hwang, C.-L., & Yoon, K. (1981). Multiple Attribute Decision Making (Vol. 186). Berlin, Heidelberg: Springer Berlin Heidelberg. Retrieved from https://doi.org/10.1007/978-3-642-48318-9
Ic, Y. T. (2014). A TOPSIS based design of experiment approach to assess company ranking. Applied Mathematics and Computation, 227, 630–647. https://doi.org/10.1016/j.amc.2013.11.043
Karimi, A. R., Mehrdadi, N., Hashemian, S. J., Bidhendi, G. R. N., & Moghaddam, R. T. (2011). Selection of wastewater treatment process based on the analytical hierarchy process and fuzzy analytical hierarchy process methods. International Journal of Environmental Science & Technology, 8(2), 267–280. https://doi.org/10.1007/BF03326215
Kazan, H., Karaman, E., Akcali, B. Y., & Sismanoglu, E. (2015). Assessment of TEOG Examination Success: Topsis Multi-Criteria Decision-Making Method Practice. Procedia - Social and Behavioral Sciences, 195, 915–924. https://doi.org/10.1016/j.sbspro.2015.06.371
Krohling, R. A., & Pacheco, A. G. C. (2015). A-TOPSIS – An Approach Based on TOPSIS for Ranking Evolutionary Algorithms. Procedia Computer Science, 55, 308–317. https://doi.org/10.1016/j.procs.2015.07.054
Lee, J. (2006). Empirical Analysis of Wholesale Used Car Auctions. University of California, Los Angeles.
Leong, Y. T., Tan, R. R., Aviso, K. B., & Chew, I. M. L. (2016). Fuzzy analytic hierarchy process and targeting for inter-plant chilled and cooling water network synthesis. Journal of Cleaner Production, 110, 40–53. https://doi.org/10.1016/j.jclepro.2015.02.036
Li, L., Liu, F., & Li, C. (2014). Customer satisfaction evaluation method for customized product development using Entropy weight and Analytic Hierarchy Process. Computers & Industrial Engineering, 77, 80–87. https://doi.org/10.1016/j.proeng.2011.11.2410
Li, X., Wang, K., Liu, L., Xin, J., Yang, H., & Gao, C. (2011). Application of the Entropy Weight and TOPSIS Method in Safety Evaluation of Coal Mines. Procedia Engineering, 26, 2085–2091. https://doi.org/10.1016/j.proeng.2011.11.2410
Lima Junior, F. R., Osiro, L., & Carpinetti, L. C. R. (2014). A comparison between Fuzzy AHP and Fuzzy TOPSIS methods to supplier selection. Applied Soft Computing, 21, 194–209. https://doi.org/10.1016/j.asoc.2014.03.014
Loetscher, T., & Keller, J. (2002). A decision support system for selecting sanitation systems in developing countries. Socio-Economic Planning Sciences, 36(4), 267–290. https://doi.org/10.1016/S0038-0121(02)00007-1
Mon, D.-L. (1995). Evaluating weapon system using fuzzy analytic hierarchy process based on entropy weight. In Fuzzy Systems, 1995. International Joint Conference of the Fourth IEEE International Conference on Fuzzy Systems and The Second International Fuzzy Engineering Symposium., Proceedings of 1995 IEEE Int (Vol. 2, pp. 591–598 vol.2). https://doi.org/10.1109/FUZZY.1995.409745
Montazar, A., Gheidari, O. N., & Snyder, R. L. (2013). A fuzzy analytical hierarchy methodology for the performance assessment of irrigation projects. Agricultural Water Management, 121, 113–123. https://doi.org/10.1016/j.agwat.2013.01.011
Nguyen, A. T., Nguyen, L. D., Le-Hoai, L., & Dang, C. N. (2015). Quantifying the complexity of transportation projects using the fuzzy analytic hierarchy process. International Journal of Project Management, 33(6), 1364–1376. https://doi.org/10.1016/j.ijproman.2015.02.007
Onat, M. G. (2007). Otomotiv Sektöründe Oranlar Yöntemi Araciliği ile Finansal Analiz (Yüksek Lisans Tezi). Marmara Üniversitesi, İstanbul.
Ozgormus, E., Mutlu, O., & Guner, H. (2005). Bulanık AHP İle Personel Seçimi. İstanbul Ticaret Üniversitesi. Retrieved from http://acikerisim.ticaret.edu.tr:8080/xmlui/handle/11467/773
Padma, T., & Balasubramanie, P. (2011). A fuzzy analytic hierarchy processing decision support system to analyze occupational menace forecasting the spawning of shoulder and neck pain. Expert Systems with Applications, 38(12), 15303–15309. https://doi.org/10.1016/j.eswa.2011.06.037
Percin, S., & Cakir, S. (2013). AB Ülkeleri’nde Bütünleşik Entropi Ağırlık-Topsis Yöntemiyle Ar-Ge Performansının Ölçülmesi. Uludağ Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi, 32(1), 77–95.
Roshandel, J., Miri-Nargesi, S. S., & Hatami-Shirkouhi, L. (2013). Evaluating and selecting the supplier in detergent production industry using hierarchical fuzzy TOPSIS. Applied Mathematical Modelling, 37(24), 10170–10181. https://doi.org/10.1016/j.apm.2013.05.043
Ruiz-Padillo, A., Torija, A. J., Ramos-Ridao, A. F., & Ruiz, D. P. (2016). Application of the fuzzy analytic hierarchy process in multi-criteria decision in noise action plans: Prioritizing road stretches. Environmental Modelling & Software, 81, 45–55. https://doi.org/10.1016/j.envsoft.2016.03.009
Sang, X., Liu, X., & Qin, J. (2015). An analytical solution to fuzzy TOPSIS and its application in personnel selection for knowledge-intensive enterprise. Applied Soft Computing, 30, 190–204. https://doi.org/10.1016/j.asoc.2015.01.002
Sengul, U., Eren, M., Eslamian Shiraz, S., Gezder, V., & Sengul, A. B. (2015). Fuzzy TOPSIS method for ranking renewable energy supply systems in Turkey. Renewable Energy, 75, 617–625. https://doi.org/10.1016/j.renene.2014.10.045
Senouci, M. A., Mushtaq, M. S., Hoceini, S., & Mellouk, A. (n.d.). TOPSIS-based dynamic approach for mobile network interface selection. Computer Networks. https://doi.org/10.1016/j.comnet.2016.04.012
Shemshadi, A., Shirazi, H., Toreihi, M., & Tarokh, M. J. (2011). A fuzzy VIKOR method for supplier selection based on entropy measure for objective weighting. Expert Systems with Applications, 38(10), 12160–12167. https://doi.org/10.1016/j.eswa.2011.03.027
Sofyalioglu, C., & Kartal, B. (2012). The Selection of Global Supply Chain Risk Management Strategies by Using Fuzzy Analytical Hierarchy Process – A Case from Turkey. Procedia - Social and Behavioral Sciences, 58, 1448–1457. https://doi.org/10.1016/j.sbspro.2012.09.1131
Tang, Y.-C., & Chang, C.-T. (2012). Multicriteria decision-making based on goal programming and fuzzy analytic hierarchy process: An application to capital budgeting problem. Knowledge-Based Systems, 26, 288–293. https://doi.org/10.1016/j.knosys.2011.10.005
Tasri, A., & Susilawati, A. (2014). Selection among renewable energy alternatives based on a fuzzy analytic hierarchy process in Indonesia. Sustainable Energy Technologies and Assessments, 7, 34–44. https://doi.org/10.1016/j.seta.2014.02.008
Thomas L Saaty. (1980). The Analytic Hierarchy Process. New York: McGraw-Hill. Retrieved from http://www.alibris.com/The-Analytic-Hierarchy-Process-Planning-Priority-Setting-Resource-Allocation-Thomas-L-Saaty/book/303071
Tiryaki, F., & Ahlatcioglu, B. (2009). Fuzzy portfolio selection using fuzzy analytic hierarchy process. Information Sciences, 179(1–2), 53–69. https://doi.org/10.1016/j.ins.2008.07.023
Uygun, O., Demir, H. I., & Erkan, E. F. (2016). Influential Analysis, Prioritization and Mapping of Strategic Goals with Fuzzy Dematel: An Empirical Case Study in a Turkish University. MATTER: International Journal of Science and Technology, 2(1), 39–58. https://doi.org/10.20319/Mijst.2016.s21.3958
Vinodh, S., Prasanna, M., & Hari Prakash, N. (2014). Integrated Fuzzy AHP–TOPSIS for selecting the best plastic recycling method: A case study. Applied Mathematical Modelling, 38(19–20), 4662–4672. https://doi.org/10.1016/j.apm.2014.03.007
Wang, Q., Wang, H., & Qi, Z. (2016). An application of nonlinear fuzzy analytic hierarchy process in safety evaluation of coal mine. Safety Science, 86, 78–87. https://doi.org/10.1016/j.ssci.2016.02.012
Yari, G., & Chaji, A. R. (2012). Maximum Bayesian entropy method for determining ordered weighted averaging operator weights. Computers & Industrial Engineering, 63(1), 338–342. https://doi.org/10.1016/j.cie.2012.03.010
Yilmaz, E. (2012). Bulanık AHP-VIKOR Bütünleşik Yöntemi İle Tedarikçi Seçimi. İktisadi ve İdari Bilimler Dergisi, 33(2), 331–354. https://doi.org/10.14780/iibd.75819
Yilmaz, M. R. (1978). Multiattribute utility theory: A survey. Theory and Decision, 9(4), 317–347. https://doi.org/10.1007/BF00126471
Zou, Z., Yun, Y., & Sun, J. (2006). Entropy method for determination of weight of evaluating indicators in fuzzy synthetic evaluation for water quality assessment. Journal of Environmental Sciences, 18(5), 1020–1023. https://doi.org/10.1016/S1001-0742(06)60032-6
Downloads
Published
How to Cite
Issue
Section
License
Copyright of Published Articles
Author(s) retain the article copyright and publishing rights without any restrictions.
All published work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.