Abstract Project portfolio evaluation and selection is a complex task involving an exhaustive assessment of competing projects with interdependencies and synergies based on multiple and often conflicting criteria. The additional factor of uncertainty further complicates this complex task. This study proposes a two-stage hybrid multi-criteria decision making and mixed-integer linear programming for evaluating and selecting projects with interdependencies under uncertainty. In Stage I, we use the fuzzy technique for order of preference by similarity to ideal solution (TOPSIS) to evaluate the alternative projects under uncertainty. In Stage II, we formulate a bi-objective mixed-integer linear program to optimize profit and qualitative values for each portfolio by considering project synergies, human resources capabilities, and employee training opportunities under different scenarios. The proposed model produces portfolios with quantitative and qualitative values for each scenario under consideration. We demonstrate and validate the applicability and efficacy of the proposed approach through a real-world case study in the cybersecurity industry.

中文翻译：

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不确定性下项目评估和选择的一种新的动态两阶段数学规划模型

摘要 项目组合评估和选择是一项复杂的任务，涉及基于多个且经常相互冲突的标准对具有相互依赖性和协同作用的竞争项目进行详尽的评估。额外的不确定因素使这项复杂的任务进一步复杂化。本研究提出了一种两阶段混合多标准决策和混合整数线性规划，用于评估和选择不确定性下具有相互依赖性的项目。在第一阶段，我们使用模糊技术按与理想解决方案的相似性（TOPSIS）进行优先排序，以评估不确定性下的替代项目。在第二阶段，我们制定了一个双目标混合整数线性计划，通过考虑项目协同效应、人力资源能力、以及不同场景下的员工培训机会。提议的模型为所考虑的每个场景生成具有定量和定性值的投资组合。我们通过网络安全行业的真实案例研究证明并验证了所提议方法的适用性和有效性。