Affiliations: Department of Production and Systems, University of
Minho, Azurém Campus, 4800-058 Guimarães, Portugal. Tel.: +35 1 253 5103
40; Fax: +35 1 253 5103 43; E-mail: [email protected] | UNINOVA, Center of Intelligent Robotics, 2829-516
Caparica, Portugal. Tel.: +35 1 212 9496 25; Fax: +35 1 212 9412 53; E-mail:
[email protected]
Note: [] Corresponding author
Abstract: Simulated Annealing (SA) is a reasonable algorithm for solving
optimization problems, through the selection of the best solution among a
finite number of possible solutions. It is a particularly attractive technique
to solve fuzzy optimization problems, because it allows finding near-optimal
solutions, which, in a fuzzy environment, is usually good enough and without a
large computational effort. We present a representative set of problems for
testing the SA algorithm suitability and performance. The SA performance is
measured in terms of the objective function values, considering several
trade-offs on constraints satisfaction levels, and computational time to
achieve a solution. Furthermore, we discuss the parameters that control the SA
algorithm to show how easily they can be manipulated. The set of fuzzy
optimization problems tested were formulated following the complete
fuzzification method proposed by Ribeiro and Moura-Pires (1999). The results
obtained show the flexibility and adaptability of the SA algorithm to solve
fuzzy optimization problems.
