An Efficient Algorithm for Non-Point Source Pollution Management Problems

A dynamic programming (DP) algorithm is proposed for a class of non-point source pollution control problems. The formulation deals with the selection of a spatial distribution of management practices in such a way as to meet a control agency's sediment pollution target. The inherently combinatorial nature of these problems — stemming from the discrete nature of the decision variables, which are production, conservation and mechanical control practices — gives them a special integer programming structure. This paper focuses on the DP formulation and the computer implementation of this algorithm. The approach is shown to be informative, robust and relatively efficient. Furthermore, the paper demonstrates that dynamic programming can be used to generate sensitivity analysis information for multiple-choice knapsack problems.