International Conference on Stochastic Programming to be held at the University of Michigan in Ann Arbor, Michigan, August 13-18, 1989.

战略、运营和实时控制决策通常是在没有关于这些决策影响的完整信息的情况下做出的。随机规划模型将这种不确定性明确地纳入决策过程。这些模型将不确定性量化为关于关键模型参数的分布信息，并针对反映决策者的目标和风险敏感性的目标。在支持模型的理论和该理论的计算机实现方面的进步将随机规划带入了广泛的实际应用的门槛。国际随机编程会议将通过召集该领域的主要研究人员分享他们的个人研究结果，从思想交流中获得见解，并侧重于可以从随机编程中受益的选定应用，来推动这一发展。这次会议将通过邀请来自世界各地的科学家参加，延续该领域真正国际合作的强大传统。

Strategic, operational, and real-time control decisions are often made without complete information about the effects of these decisions. Stochastic programming models incorporate this uncertainty explicitly into the decision-making process. These models quantify uncertainty into distributional information on key model parameters and address an objective that reflects the goals and risk sensitivity of the decision maker. Advances in the theory supporting the models and in computer implementations of this theory have brought stochastic programming to the threshold of widespread, practical use. The International Conference on Stochastic Programming will further this development by bringing together the leading researchers in the field to share their individual findings, to gain insights from the exchange of ideas, and to focus on selected applications that can benefit from stochastic programming. This conference will continue the field's strong tradition of truly international cooperation by including scientists from around the world.