Abstract
Fuzzy set theory was first developed in order to solve imprecise or vague problems in the field of artificial intelligence, especially for imprecise reasoning and modeling linguistic terms. Stemming from research by Tanaka et al (1974), a number of fuzzy linear programming models have been developed. Lai and Hwang (1992) have classified linear programming models with imprecise information into two main classes: fuzzy linear programming, and possibilistic programming. As an extension, nonlinear programming models with imprecise information should be transferred into an equivalent crisp nonlinear programming problem, and then solved by conventional solution techniques or packages of nonlinear programming.
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© 1999 Springer-Verlag Berlin Heidelberg
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Chen, HK. (1999). Fuzzy/Dynamic User-Optimal Route Choice Model. In: Dynamic Travel Choice Models. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-59980-4_13
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DOI: https://doi.org/10.1007/978-3-642-59980-4_13
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-64207-4
Online ISBN: 978-3-642-59980-4
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