SELECTION OF DEFUZZIFICATION METHOD TO OBTAIN CRISP VALUES FOR REPRESENTING UNCERTAIN DATA IN A MODIFIED SWEEP ALGORITHM
A study of using fuzzy-based parameters for solving public bus routing problem with uncertain demand is presented. 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 user’s preference. Fuzzy inference rules are assigned to relate the fuzzy parameters to the crisp values which are concerned in the route selection process. 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.
D. H. Rao, S. S. Saraf, Study of Defuzzification Methods of Fuzzy Logic Controller for Speed Control of a DC Motor, IEEE Transactions, pp. 782-787, 1995.
D. Teodorovic, G. Pavkovic, A Simulated Annealing Technique Approach to the Vehicle Routing Problem in the Case of the Stochastic, Transportation Planning Technology, vol. 16, pp. 261-273, 1992.
D. Teodorovic, G. Pavkovic, “The fuzzy set theory approach to the vehicle routing problem when demand at nodes is uncertain”, Fuzzy Sets and Systems, vol. 82, pp. 307-317, 1996.
E. Mamdani, S. Assilian, An experiment in linguistic synthesis with a fuzzy logic controller, Internat. J. Man-Machine Studies vol. 7, pp. 1-13, 1975.
G. J. Klir, B. Yuan, Fuzzy Sets and Fuzzy Logic: Theory and Applications, Prentice Hall PTR, New Jersey, 1995.
G. J. Klir, U. H. St. Clair, and B. Yuan, Fuzzy Set Theory: Foundations and Applications, Prentice Hall, Upper Saddle River, NJ, 1997.
Gunadi W. Nurcahyo, Siti Mariyam Shamsuddin, Rose Alinda Alias, M. Noor Md. Sap, Vehicle Routing Problem for Public Transport: A Case Study, International Technical Conf. on Computers/Systems, Circuits and Communications, vol. 2, pp. 1180-1183, Phuket, Thailand, 16-19 July 2002.
S. Kagaya, S. Kikuchi, R. A. Donnelly, Use of a Fuzzy Theory Technique for Grouping of Trips in the Vehicle Routing and Scheduling Problem, European Journal of Opl. Res., vol. 76, pp. 143-154, 1994.
T. A. Runkler, Extended Defuzzification Methods and Their Properties, IEEE Transactions, pp. 694-700, 1996.
T. A. Runkler, Selection of Appropriate Defuzzification Methods using Application Specific Properties, IEEE Transactions on Fuzzy Systems, vol. 5, no. 1, pp. 72-79, 1997.
T. A. Runkler, M. Glesner, Defuzzification with Improved Static and Dynamic Behavior: Extended Center of Area, European Congress on Fuzzy and Intelligent Technologies, pp. 845-851, Aachen, Sept., 1993.
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.