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水库优化调度问题是根据预报的降水和入流以获得最优的水库泄水、蓄水和下游河段的通航流量。本文研究了5种使偏离一组选定的目标蓄水和流量值的偏差成极小的目的规划方案:(1)抢先的目的规划;(2)加权目的规划;(3)最小最大目的规划;(4)模糊目的规划和(5)区间目的规划。水库调度问题也可以用公式示为多目标线性规划(MOLP)。目的规划的最优解包含在MOLP的有效点中。也表明了最小最大和模糊目的规划可能产生无效点作为最优值;然而存在另外可供选择的有效最优值。因为目的规划集中于达到预先确定的主观目标值,也许不可能发现客观潜在的最优值。无目标约束的可行域中的极值点检验克服了这种困难并提供了一种建立实际目标值的方法。这些方法已应用于肯塔基的格林河流域,其成果曾由以前的研究者报道过。
The problem of reservoir optimal scheduling is based on the predicted rainfall and inflow to obtain the optimal reservoir discharge, impoundment and navigation flow in the downstream reach. In this paper, we study five approaches to minimize the deviations from a set of selected target impoundment and flow values: (1) preemptive destination planning; (2) weighted destination planning; (3) minimum and maximum destination planning ; (4) fuzzy goal planning and (5) interval goal planning. Reservoir scheduling problems can also be formulated as multi-objective linear programming (MOLP). The optimal solution to the goal plan is included in the effective point of MOLP. It is also shown that the min-max and fuzzy-objective programming may produce invalid points as the optimal values; however, there are other valid optimal values to choose from. Because the goal planning focuses on reaching a predetermined subjective target value, it may not be possible to find an objectively latent optimal value. The extreme point test in the feasible region without the goal constraint overcomes this difficulty and provides a way to establish the actual target value. These methods have been applied to the Green River Basin in Kentucky and the results have been reported by previous researchers.