Given some data, which consists of pairs of fuzzy numbers, our evolutionary algorithm searches our library of fuzzy functions (which includes linear, polynomial, exponential and logarithmic) for a fuzzy function which best ΓΏts the data. Tests of our fuzzy regression package are given for each of the
Evolutionary algorithm solution to fuzzy problems: Fuzzy linear programming
β Scribed by James J. Buckley; Thomas Feuring
- Publisher
- Elsevier Science
- Year
- 2000
- Tongue
- English
- Weight
- 317 KB
- Volume
- 109
- Category
- Article
- ISSN
- 0165-0114
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β¦ Synopsis
In this paper we wish to ΓΏnd solutions to the fully fuzziΓΏed linear program where all the parameters and variables are fuzzy numbers. We ΓΏrst change the problem of maximizing a fuzzy number, the value of the objective function, into a multi-objective fuzzy linear programming problem. We prove that fuzzy exible programming can be used to explore the whole undominated set to the multi-objective fuzzy linear program. An evolutionary algorithm is designed to solve the fuzzy exible program and we apply this program to two applications to generate good solutions.
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