Abstract
Optimizing system reliability in a fuzzy environment is complex due to the presence of
imprecise multiple decision criteria such as maximizing system reliability and minimizing system cost.
This calls for multi-criteria decision making approaches that incorporate fuzzy set theory concepts and
heuristic methods. This paper presents a fuzzy multi-criteria nonlinear model, and proposes a fuzzy
multi-criteria genetic algorithm (FMGA) for complex bridge system reliability design in a fuzzy
environment. The algorithm uses fuzzy multi-criteria evaluation techniques to handle fuzzy goals,
preferences, and constraints. The evaluation approach incorporates fuzzy preferences and expert
choices of the decision maker in regards to cost and reliability goals. Fuzzy evaluation gives the
algorithm flexibility and adaptability, yielding near-optimal solutions within short computation times.
Results from computational experiments based on benchmark problems demonstrate that the FMGA
approach is a more reliable and effective approach than best known algorithm, especially in a fuzzy
multi-criteria environment.