Penalty-Free Evolutionary Algorithm Optimization for the Long Term Rehabilitation and Upgrading of Water Distribution Systems

摘要

The rehabilitation and upgrading of a water distribution system (WDS) involves a great amount of capital and hence the optimization of factors such as the phasing, timing and magnitude of the upgrading with regard to cost is a necessity. This paper presents a penalty-free multi-objective evolutionary algorithm (PFMOEA) model for the optimal long term upgrading of water distribution systems. The model couples a pressure dependent analysis within a multi-objective optimization frame work and has proven to be effective and efficient in locating the optimal/ near optimal solution. Herein, a real life network in Wobulenzi was used to demonstrate the efficacy of the model. Results generated by PFMOEA and the conventional linear programming (LP) are presented and compared. It is shown that PFMOEA outperforms LP in that it succeeded in finding lower network rehabilitation and upgrading cost.