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A differential evolution algorithm for the resource investment problem with discounted cash flows

机译:贴现现金流量的资源投资问题的差分演变算法

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The resource investment problem with discounted cash flows is investigated in this paper. Its objective is to find a schedule and the resource requirement levels that the net present value of the project cash flows is maximized. We propose a self-adaptive differential evolution algorithm with two local search operators to solve this problem. We design the evolutionary operators such as mutation, crossover, local search, and immigration. By employing the proposed algorithm to solve 960 problems, we make a comparison with the genetic algorithm, which has been employed to solve this problem. Moreover, we design a local search operator and compare it with an existing local search operator, and the results show it is a very effective operator to solve this problem. In summary, the experimental results are quite satisfactory.
机译:本文调查了贴现现金流量的资源投资问题。其目标是找到一个计划和资源要求水平,即项目现金流量的净目前最大化。我们提出了一种具有两个本地搜索操作员的自适应差分演进算法来解决这个问题。我们设计了突变,交叉,本地搜索和移民等进化运营商。通过采用所提出的算法来解决960个问题,我们与遗传算法进行比较,这些遗传算法已被用于解决这个问题。此外,我们设计了本地搜索操作员并将其与现有的本地搜索操作员进行比较,结果表明它是一个非常有效的操作员来解决这个问题。总之,实验结果非常令人满意。

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