Collaborative Research: Design Principles for Parallel Simulation Optimization

该奖项提供资金，以促进在并行计算平台上解决模拟优化(SO)问题的算法设计。因此，问题是优化问题，其中目标函数和约束条件只能通过随机模拟来观察。几乎所有当前用于解决SO问题的算法都假设单个处理器作为计算平台。然而，计算设备的趋势是多处理器计算机，不仅是笔记本电脑/台式机计算机，而且一直到云计算环境。这项研究将探索如何设计算法来解决利用这种环境的SO问题，试图以合理的成本和合理的时间返回高质量的解决方案。如果成功，这项研究的结果将导致一条新的研究路线-并行SO-随之而来的是对并行计算平台上SO算法的设计和实现的改进，从而使这项当前计算密集型技术更容易获得和更有效。SO已经在应用领域占据了重要地位，现有的试验床www.simopt.org中存在的各种SO问题就证明了这一点。拟议的研究将通过可靠地解决重要的SO问题，为产生重大影响提供进一步的机会。这项研究是通过创造方法、理论和计算工具来促进更大、更现实的SO问题的自动解决来增强SO的可实施性的持续努力的一部分。

This award provides funding to advance the design of algorithms for solving simulation-optimization (SO) problems on parallel computing platforms. SO problems are optimization problems where the objective function and constraints can only be observed through a stochastic simulation. Virtually all current algorithms for solving SO problems assume a single processor as the computing platform. However, the trend in computing devices is towards multi-processor computers, not just at the laptop/desktop level, but all the way up to cloud computing environments. This research will explore how to design algorithms for solving SO problems that exploit such environments, to attempt to return high-quality solutions at a reasonable cost and within a reasonable amount of time.If successful, the results of this research will lead to a new line of research - parallel SO - with ensuing improvements in the design and implementation of SO algorithms on parallel computing platforms, thus making this currently computing-intensive technology much more accessible and effective. SO already holds an important place in application fields, as evidenced by the variety of SO problems in an existing testbed www.simopt.org. The proposed research will provide further opportunities for major impact through reliable solution of important SO problems. This research is part of a continuing thrust to enhance the implementability of SO by creating methods, theory, and computational tools to facilitate the automatic solution of larger and more realistic SO problems.