Previous |  Up |  Next

Article

Title: Fuzzy linear programming via simulated annealing (English)
Author: Ribeiro, Rita Almeida
Author: Pires, Fernando Moura
Language: English
Journal: Kybernetika
ISSN: 0023-5954
Volume: 35
Issue: 1
Year: 1999
Pages: [57]-67
Summary lang: English
.
Category: math
.
Summary: 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. (English)
Keyword: fuzzy optimization
Keyword: simulated annealing
MSC: 90C08
MSC: 90C59
MSC: 90C70
idZBL: Zbl 1274.90524
idMR: MR1705530
.
Date available: 2009-09-24T19:23:15Z
Last updated: 2015-03-27
Stable URL: http://hdl.handle.net/10338.dmlcz/135267
.
Reference: [1] Bellman R. D., Zadeh L. A.: Decision–making in a fuzzy environment.Management Sci. 17 (1970), 4, 141–164 Zbl 0224.90032, MR 0301613, 10.1287/mnsc.17.4.B141
Reference: [2] Connoly D. T.: An improved annealing scheme for the QAP.European J. Oper. Res. 46 (1990), 93–100 MR 1053816, 10.1016/0377-2217(90)90301-Q
Reference: [3] Connoly D.: General purpose simulated annealing.J. Oper. Res. Soc. 43 (1992), 5, 495–505 10.1057/jors.1992.75
Reference: [4] Eglese R. W.: Simulated annealing: A tool for operational research.European J. Oper. Res. 46 (1990), 271–281 Zbl 0699.90080, MR 1064622, 10.1016/0377-2217(90)90001-R
Reference: [5] Ishibuchi H., Tanaka H., Misaki S.: Fuzzy flow shop scheduling by simulated annealing.In: Fuzzy Optimization (M. Delgado, ed.), Physica–Verlag, Berlin 1994 Zbl 0823.90139, MR 1315076
Reference: [6] Kickert W. J. M.: Fuzzy Theories on Decision Making.Frontiers in Systems Research, Vol 3. Martinus Nijhoff Social Sciences Division 1978 Zbl 0427.90059, MR 0565857
Reference: [7] Kirkpatrick S., Gelatt C. D., Vecchi M. P.: Optimization by simulated annealing.Science 220 (1983), 4598, 671–680 Zbl 1225.90162, MR 0702485, 10.1126/science.220.4598.671
Reference: [8] Lai Y.-J., Hwang C.-L.: Fuzzy Multiple Objective Decision Making.(Lecture Notes in Economics and Mathematical Systems.) Springer–Verlag, Berlin 1994 Zbl 0823.90070, MR 1266628
Reference: [9] Pires F. M., Moura J. Pires, Ribeiro R. A.: Solving fuzzy optimisation problems: Flexible approaches using simulated annealing.In: ISSCI’96, Montpelier 1996
Reference: [10] Ribeiro R. A., Pires F. M.: Fuzzy site location problems and simulated annealing.In: Series Studies in Locational Analysis (B. Boffey and E. Declerque, eds.), to appear
Reference: [11] Zeleny M.: Fuzziness, knowledge and optimization: New optimality concepts.In: Fuzzy Optimization (M. Delgado, J. Kacprzyk, J.-L. Verdegay and M. A. Vila, eds.), Physica–Verlag, Berlin 1994 Zbl 0826.90137, MR 1315053
Reference: [12] Zimmermann H.-J.: Fuzzy programming and linear programming with several objective functions.Fuzzy Sets and Systems 1 (1978), 45–55 Zbl 0364.90065, MR 0496734, 10.1016/0165-0114(78)90031-3
Reference: [13] Zimmermann H.-J.: Fuzzy Set Theory and its Applications.Third edition. Kluwer, Boston 1986 Zbl 0984.03042, MR 0814498
.

Files

Files Size Format View
Kybernetika_35-1999-1_6.pdf 1.447Mb application/pdf View/Open
Back to standard record
Partner of
EuDML logo