Probabilistic multi-objective optimal design of composite channels using particle swarm optimization

To achieve cost effectiveness and reliability in design, this paper presents a probabilistic multi-objective model for optimal design of composite channels that have a cross-sectional shape of horizontal bottom and parabolic sides. The multiple objectives of channel design include minimizing the cost of channel construction, maximizing the probability of the expected channel capacity being greater than the design flow and minimizing the overtopping probability. In this study, the principles of first-order uncertainty analysis are adopted for handling uncertainty in parameters of the problem. The optimization model is solved using the particle swarm optimization method and Pareto-optimal solutions are generated for various combinations of overtopping probability and exceedance probability of channel capacity. The results show that the presented approach has good potential for exploring different alternative designs of open channels under input parameter uncertainty.