In recent years, the Quebec government has highlighted the importance of making decisions that are both sustainable and robust under climate change uncertainties. This paper aims to answer the following question: How to sort the alternatives according to their degree of sustainability achievement while evaluations are uncertain and temporal? The general objective of the paper is to propose a first temporal sorting method under stochastic uncertainty. The proposed method, called TSMAA-Tri, will assign each alternative to a predefined category based on a generalization of SMAA-Tri to a temporal context (multi-period evaluation of alternatives) where alternative evaluations are stochastic. The method starts performing Monte Carlo simulations to generate stochastic evaluation values. Each simulation (scenario of uncertainty) will generate a specific value for each criterion using the corresponding probability distribution. Then, aggregation consists in applying SMAA Tri at each period and performing a triple aggregation: (a) uncertainty aggregation; (b) multi-criteria aggregation; and (c) temporal aggregation. Multi-criteria aggregation consists in applying the SMAA-TRI method at each period. Then, two ways of temporal aggregation are proposed, based either on acceptability index or on outranking index of boundary profile. The proposed method is illustrated for sustainable forest management to show its applicability.

中文翻译：

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TSMAA-TRI：不确定性下的时间多标准排序方法

近年来，魁北克政府强调了在气候变化的不确定性下做出既可持续又稳健的决策的重要性。本文旨在回答以下问题：在评估具有不确定性和时间性的情况下，如何根据备选方案的可持续性成就程度对其进行排序? 本文的总体目标是提出一种随机不确定性下的第一种时间排序方法。所提出的方法称为 TSMAA-Tri，将基于 SMAA-Tri 对时间上下文（备选方案的多周期评估）的泛化，将每个备选方案分配给预定义的类别，其中备选方案评估是随机的。该方法开始执行蒙特卡罗模拟以生成随机评估值。每个模拟（不确定性场景）将使用相应的概率分布为每个标准生成一个特定值。然后，聚合包括在每个周期应用 SMAA Tri 并执行三重聚合： (a) 不确定性聚合；(b) 多标准汇总；(c) 时间聚合。多标准聚合包括在每个时期应用 SMAA-TRI 方法。然后，提出了两种时间聚合方法，基于可接受性指数或边界轮廓的优等指数。所提出的方法被说明用于可持续森林管理，以显示其适用性。