A common approach to modeling project interactions in multiattribute project portfolio selection is to augment the additive portfolio utility function, in which portfolio utility is the sum of the included projects’ utilities, with additional terms representing the synergy/cannibalization effects triggered by selecting specific subsets of projects. In this paper we develop a set of sufficient and necessary assumptions for representing preferences among multiattribute project portfolios with a quasi-symmetric multilinear utility function and show how this function gives rise to interpreting interaction effects as additional terms in the additive portfolio utility function. To foster practical applicability of these theoretical contributions, we also develop techniques to elicit such portfolio utility functions as well as optimization models to identify the feasible portfolio that satisfies relevant resource and other constraints with the maximal expected utility. In recognition that incorporating project interactions necessitates increased involvement of decision makers in assessing the interaction effects and results in computationally more challenging portfolio optimization problems, we analyze the importance of modeling interactions through series of simulation studies based on randomly generated and real-world data sets. Specifically, we examine the impact that omitting project interactions has on the project-level decision recommendations and on the expected utility of the recommended portfolio.

中文翻译：

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多属性组合决策分析中的项目交互建模：公理基础和实际意义

在多属性项目组合选择中对项目交互进行建模的常见方法是增强附加组合效用函数，其中组合效用是所包含项目效用的总和，附加项表示通过选择特定子集触发的协同/蚕食效应项目。在本文中，我们提出了一组充分且必要的假设，用于用准对称多线性效用函数表示多属性项目组合之间的偏好，并展示该函数如何将交互效应解释为加性投资组合效用函数中的附加项。为了促进这些理论贡献的实际适用性，我们还开发了引出此类投资组合效用函数的技术以及优化模型，以确定满足相关资源和其他约束以及最大预期效用的可行投资组合。认识到纳入项目交互需要决策者更多地参与评估交互效果，并导致计算上更具挑战性的投资组合优化问题，我们通过基于随机生成的真实世界数据集的一系列模拟研究来分析建模交互的重要性。具体来说，我们研究了省略项目交互对项目级决策建议和推荐组合的预期效用的影响。