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Selection of defuzzification method to obtain crisp value for representing uncertain data in a modified sweep algorithm
Keywords:
sweep algorithm, public bus routing, route selection, fuzzy-based parameter, defuzzificationAbstract
We present a study of using fuzzy-based parameters for solving public bus routing problem where demand is uncertain. The fuzzy-based parameters are designed to provide data required by the route selection procedure. The uncertain data are represented as linguistic values which are fully dependent on the users preference. This paper focuses on the selection of the Defuzzification method to discover the most appropriate method for obtaining crisp values which represent uncertain data. We also present a step by step evaluation showing that the fuzzy-based parameters are capable to represent uncertain data replacing the use of exact data which common route selection algorithms usually use.
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References
[1] G. W. Nurcahyo, Siti Mariyam Shamsuddin, Rose Alinda Alias, M. Noor Md. Sap, ìVehicle Routing Problem for Public Transport: A Case Studyî, International Technical Conf. on Computers/Systems, Circuits and Communications, Vol. 2, pp. 1180-1183, Phuket, Thailand, 16-19 July 2002.
[2] B. E. Gillet, L. R. Miller, ìA Heuristic Algorithm for the Vehicle Dispatch Problemî, Operation Research, Vol. 22, 1974, pp. 340-349.
[3] D. Teodorovic, G. Pavkovic, ìThe fuzzy set theory approach to the vehicle routing problem when demand at nodes is uncertainî, Fuzzy Sets and Systems, Vol. 82, 1996, pp. 307-317.
[4] D. H. Rao, S. S. Saraf, ìStudy of Defuzzification Methods of Fuzzy Logic Controller for Speed Control of a DC Motorî, IEEE Transactions, 1995, pp. 782-787.
[5] E. Mamdani, S. Assilian, An experiment in linguistic synthesis with a fuzzy logic controller, Internat. J. Man-Machine Studies, Vol. 7, 1975, pp. 1-13.
[6] T. A. Runkler, ìExtended Defuzzification Methods and Their Propertiesî, IEEE Transactions, 1996, pp. 694-700.
[2] B. E. Gillet, L. R. Miller, ìA Heuristic Algorithm for the Vehicle Dispatch Problemî, Operation Research, Vol. 22, 1974, pp. 340-349.
[3] D. Teodorovic, G. Pavkovic, ìThe fuzzy set theory approach to the vehicle routing problem when demand at nodes is uncertainî, Fuzzy Sets and Systems, Vol. 82, 1996, pp. 307-317.
[4] D. H. Rao, S. S. Saraf, ìStudy of Defuzzification Methods of Fuzzy Logic Controller for Speed Control of a DC Motorî, IEEE Transactions, 1995, pp. 782-787.
[5] E. Mamdani, S. Assilian, An experiment in linguistic synthesis with a fuzzy logic controller, Internat. J. Man-Machine Studies, Vol. 7, 1975, pp. 1-13.
[6] T. A. Runkler, ìExtended Defuzzification Methods and Their Propertiesî, IEEE Transactions, 1996, pp. 694-700.
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Published
2003-10-01
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[1]
“Selection of defuzzification method to obtain crisp value for representing uncertain data in a modified sweep algorithm”, JCS&T, vol. 3, no. 02, pp. p. 22–28, Oct. 2003, Accessed: Mar. 08, 2026. [Online]. Available: https://journal.info.unlp.edu.ar/JCST/article/view/934
