In the present work, a model is presented for the optimization of water distribution networks (WDN). The developed model can be used to verify node pressures, head losses, and fluid flow rate and velocity in each pipe...
详细信息
In the present work, a model is presented for the optimization of water distribution networks (WDN). The developed model can be used to verify node pressures, head losses, and fluid flow rate and velocity in each pipe. The algorithm is based on particle swarm optimization (PSO), considering real and discrete variables and avoiding premature convergence to local optima using objective function penalization. The model yields the minimum cost of the network, the node pressures and the velocities in the pipes. The pressures and velocities are calculated using the hydraulic simulator Epanet. Some benchmark problems are used to test the applicability of the developed model, considering WDN for small-, medium-, and large-scale problems. Obtained results are consistent with those found in the literature.
In order to improve the efficiency of the branch-and-bound method for mixed-discrete nonlinear programming, a non-uniform convergence tolerance scheme is proposed for the continuous subproblem optimizations. The sugge...
详细信息
In order to improve the efficiency of the branch-and-bound method for mixed-discrete nonlinear programming, a non-uniform convergence tolerance scheme is proposed for the continuous subproblem optimizations. The suggested scheme assigns the convergence tolerances for each continuous subproblem optimization according to the maximum constraint violation obtained from the first iteration of each subproblem optimization in order to reduce the total number of function evaluations needed to reach the discrete optimal solution. The proposed tolerance scheme is integrated with five branching order options. The comparative performance test results using the ten combinations of the five branching orders and two convergence tolerance schemes show that the suggested non-uniform convergence tolerance scheme is obviously superior to the uniform one. The results also show that the branching order option using the minimum clearance difference method performed best among the five branching order options. Therefore, we recommend using the "minimum clearance difference method" for branching and the "non-uniform convergence tolerance scheme" for solving discrete optimization problems.
暂无评论