With the restriction of water demand and supply, the objective function optimal value was calculated by sequential quadratic programming. 以需水量和可供水量為約束條件，採用序列二次規劃法求解函數最優值。
The proposed approach is robust to local minima of the energy functional because it is minimized by dynamic programming method in the whole energy space. 由於採用了動態規劃法並在整個能量空間中搜索能量泛函的極值，演算法對能量泛函的局部極值有較強的魯棒性。
