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Stochastic multicriteria acceptability analysis (SMAA) is a family of multiple criteria decision making (MCDM) methods dealing with incomplete, imprecise, and uncertain information on the evaluations and preference model parameters. As it provides a general framework that has extensions to deal with various specificities in MCDM problems, the development of SMAA methods and their applications in real-life decision-making problems have been increased over the recent years. This paper provides an up-to-date literature review of different SMAA methods and their applications in various areas. First, we selected, from different on-line data base, 118 articles published between 1998 and 2017. We categorized the selected papers into theoretical and applied. While the theoretical papers were analyzed based on the method’s aggregation procedure, type of problem, type of method’s outputs and inputs, the applied papers were separated and analyzed by application areas. Then, we provide some descriptive statistics, analyzing the papers regarding to publication year and journals of publication. Finally, we provide some guidelines to assist decision-makers in the choice of a SMAA method on a specific decision-making context and some future research directions.

In most project portfolio selection (PPS) situations, the presence of multiple attributes and decision-maker preference is inevitable. As Multi-criteria Decision Analysis (MCDA) methods provide a framework well-suited to deal with these challenges in PPS problems, the use of MCDA methods in real-life PPS problems has increased in recent years. This paper provides a comprehensive literature review of the use of different MCDA methods and their individual or combined utilization with other modeling techniques to support PPS problems. First, we summarize how MCDA methods are used in different modeling approaches. Second, we examine the mathematical models that are generally used to combine MCDA with mathematical programming techniques to solve PPS problems with resource constraints. Third, we present the drawbacks of combined utilization and discuss recent advances. Finally, we visualize the summary of the reviewed papers as a decision tree to assist researchers and practitioners in the use of MCDA methods in a specific PPS context and propose some future research directions.

Course of action (COA) comparison is a critical step of the operation planning process whereby COAs are considered independently and evaluated against a set of criteria that are established by the staff and commander. The goal is to support the commander's decision-making process by identifying and recommending the COA that best accomplishes the mission. However, the uncertainty associated with the evaluations of the COAs and the preferences make this decision process more complicated in real-world applications. This study proposes a multiple-criteria approach based on the SMAA-PROMETHEE method that can be practically implemented to COA comparison and selection. The SMAA-PROMETHEE method performs Monte-Carlo simulations and runs PROMETHEE as the multi-criteria decision analysis (MCDA) method to investigate the robustness of COA rankings when input parameters are uncertain and incomplete. The main advantage of the approach is its ability to articulate to the commander why one COA is preferable to another by exploring the input parameter space that assigns a given COA to a certain rank. A case study is presented to demonstrate the robustness and efficiency of the proposed approach.