This paper presents the study of multi-objective optimization of a pharmaceutical portfolio when both cost and return values are uncertain. Decision makers in the pharmaceutical industry encounter several challenges in deciding the optimal selection of drug projects for their portfolio since they have to consider several key aspects such as a long product-development process split into multiple phases, high cost and low probability of success. Additionally, the optimization often involves more than a single objective (goal) with a non-deterministic nature. The aim of the study is to develop a stochastic multi-objective approach in the frame of chance-constrained goal programming. The application of the results of this study allows pharmaceutical decision makers to handle two goals simultaneously, where one objective is to achieve a target return and another is to keep the cost within a finite annual budget. Finally, the numerical results for portfolio optimization are presented and discussed.

中文翻译：

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成本与收益不确定下的多目标药物组合优化

本文介绍了在成本和回报值都不确定的情况下对制药投资组合进行多目标优化的研究。制药行业的决策者在为他们的投资组合决定最佳药物项目选择时会遇到一些挑战，因为他们必须考虑几个关键方面，例如分为多个阶段的漫长的产品开发过程、高成本和低成功概率。此外，优化通常涉及多个具有非确定性的目标（目标）。该研究的目的是在机会约束目标规划的框架内开发一种随机多目标方法。本研究结果的应用使制药决策者能够同时处理两个目标，其中一个目标是实现目标回报，另一个目标是将成本保持在有限的年度预算内。最后，介绍并讨论了投资组合优化的数值结果。