Geodesic
Fuzzy linear programming via simulated annealing
Kybernetika, Tome 35 (1999) no. 1, p. [57].

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This paper shows how the simulated annealing (SA) algorithm provides a simple tool for solving fuzzy optimization problems. Often, the issue is not so much how to fuzzify or remove the conceptual imprecision, but which tools enable simple solutions for these intrinsically uncertain problems. A well-known linear programming example is used to discuss the suitability of the SA algorithm for solving fuzzy optimization problems.
Classification : 90C08, 90C59, 90C70
Keywords: fuzzy optimization; simulated annealing 
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     author = {Ribeiro, Rita Almeida and Pires, Fernando Moura},
     title = {Fuzzy linear programming via simulated annealing},
     journal = {Kybernetika},
     pages = {[57]},
     publisher = {mathdoc},
     volume = {35},
     number = {1},
     year = {1999},
     mrnumber = {1705530},
     zbl = {1274.90524},
     language = {en},
     url = {http://geodesic.mathdoc.fr/item/KYB_1999__35_1_a5/}
}
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Ribeiro, Rita Almeida; Pires, Fernando Moura. Fuzzy linear programming via simulated annealing. Kybernetika, Tome 35 (1999) no. 1, p. [57]. http://geodesic.mathdoc.fr/item/KYB_1999__35_1_a5/