  The design of the cross-section of an FRP-reinforced concrete beam is an
iterative process of estimating both its dimensions and the reinforcement
ratio, followed by the check of the compliance of a number of strength and
serviceability constraints. The process continues until a suitable solution is
found. Since there are infinite solutions to the problem, it appears convenient
to define some optimality criteria so as to measure the relative goodness of
the different solutions. This paper intends to develop a preliminary least-cost
section design model that follows the recommendations in the ACI 440.1 R-06,
and uses a relatively new artificial intelligence technique called particle
swarm optimization (PSO) to handle the optimization tasks. The latter is based
on the intelligence that emerges from the low-level interactions among a number
of relatively non-intelligent individuals within a population.
