摘要
基于线性规划的污染负荷优化分配结果通常存在"极端化"现象,分配方案的合理性、可行性和公平性均受到影响。针对该问题,提出了一种污染负荷优化分配的非线性规模模型,以最小化污染物削减率方差为目标,允许决策者根据偏好调整最低允许负荷量,并采用遗传算法求解模型。研究结果表明,非线性规划模型能够较好地解决线性规划存在的"极端化"现象,计算结果在公平合理性方面获得较大改进,并且具有较大的弹性,有利于提供更科学、合理的污染负荷分配方案。
The linear programming model for waste load allocation usually results in extreme values, which leads to an optimal but infeasible allocation scheme. Therefore,a non-linear programming model for waste load allocation is proposed in this paper,whose goal is to minimize the variance of pollution reduction,and decision-maker is allowed to change the minimal permitted waste load. The genetic algorithm is used to establish the non-linear programming model. Study results show that the non-linear programming model can resolve the problem of extreme output created by linear programming model, and the calculation results obtain great improvement in fairness and reasonableness. Non-linear program model can provide more flexible and more scientific scheme for waste load allocation than that of traditional linear program model.
出处
《黑龙江环境通报》
2016年第4期34-37,共4页
Heilongjiang Environmental Journal
关键词
污染负荷分配
优化
非线性规划
Waste load allocation
Optimization
Non-linear programming
