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Time-cost optimization: using GA and fuzzy sets theory for uncertainties in cost

机译：时间成本优化：使用遗传算法和模糊集理论确定成本不确定性

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摘要

Uncertainties should be considered in any time-cost trade-off problems when minimizing project cost and duration, which leads to the so-called stochastic time-cost trade-off problem. A new approach to investigate stochastic time-cost trade-off problems employing fuzzy logic theory is presented. The proposed approach fully embeds the fuzzy structure of the uncertainties in total direct cost into the model. An appropriate GA is used to develop α solution to the multi-objective fuzzy time cost model. The accepted risk level of the project manager is defined through α cut approach for which a separate Pareto front with set of non-dominated solutions has been developed. To compare the alternative set of options for any assumed project duration, associated fuzzy costs for different values of α cut are ranked employing two appropriate approaches for fuzzy costs comparison. The proposed models are applied to solve two benchmark test problems. It is shown that the models facilitate the decision-making process by selecting specified risk levels and employing the associated Pareto front.
机译：在最小化项目成本和工期时，应在任何时间成本权衡问题中考虑不确定性，这会导致所谓的随机时间成本权衡问题。提出了一种利用模糊逻辑理论研究随机时间－成本权衡问题的新方法。所提出的方法将总直接成本不确定性的模糊结构完全嵌入到模型中。使用适当的遗传算法开发多目标模糊时间成本模型的α解。项目经理的可接受风险水平是通过α割方法定义的，该方法已经开发了一套带有非支配解决方案的单独的Pareto前沿。为了比较任何假定的项目工期的备选方案集，采用两种合适的方法进行模糊成本比较，对不同的αcut值的相关模糊成本进行排序。所提出的模型用于解决两个基准测试问题。结果表明，这些模型通过选择特定的风险级别并采用相关的Pareto前沿来促进决策过程。

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