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Multicriteria decisions on interdependent infrastructure transportation projects using an evolutionary-based framework

机译:使用基于演化的框架对相互依赖的基础设施运输项目进行多标准决策

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When evaluating transportation infrastructure projects and determining which of them will be carried out from a set of projects and given a budget constraint, several criteria need to be considered in the decision. Standard evaluation practices imply the aggregation of impacts into one utility function which is later optimized. Nevertheless these techniques used for translation of different measuring units into monetary terms are highly controversial. Multicriteria techniques can explicitly deal with different measuring units, however, they are not suitable to model interdependence relationships of projects that share a common characteristic (same route, location or target population, for instance). In this research we model this transportation planning problem, the multi-objective transportation infrastructure project selection problem (MTIPSP), as a constrained multi-objective optimization problem with quadratic objective functions, using a variation of the multi-objective 0-1 knapsack problem plus some additional constraints. Given the combinatorial nature of the problem, an evolutionary-based framework is used for the identification of Pareto solutions, and later, those with non-attractive properties are filtered using a Knee Identification Procedure. The final selection of the projects portfolio is made using a well known multicriteria decision aid method and including the decision makers' preferences based on the existing context.
机译:在评估运输基础设施项目并确定将在一组项目中执行哪些项目并且在预算有限的情况下,决策中需要考虑几个标准。标准评估实践意味着将影响汇总到一个效用函数中,然后对其进行优化。但是,这些用于将不同计量单位转换为货币术语的技术引起了很大争议。多准则技术可以显式地处理不同的度量单位,但是,它们不适合建模具有共同特征(例如,相同的路线,位置或目标人口)的项目的相互依赖关系。在这项研究中,我们使用多目标0-1背包问题的一种变体,将该运输规划问题(多目标运输基础设施项目选择问题(MTIPSP))建模为具有二次目标函数的约束多目标优化问题。一些其他限制。考虑到问题的组合性质,将基于进化的框架用于Pareto解决方案的识别,然后,使用膝盖识别程序对具有非吸引力属性的解决方案进行过滤。项目组合的最终选择是使用众所周知的多准则决策辅助方法进行的,其中包括基于现有上下文的决策者的偏好。

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