OPTIMIZING STAFF SCHEDULING BY MONTE CARLO SIMULATION

医疗设施经常面临人员调度困难 问题 每家医院和医疗集团都会欢迎一个功能齐全的， 计算机化 主动优化调度的解决方案。 DOCS算法-结合会计框架， 约束和 一个蒙特-卡罗刺激-作为一种新的方法， 工作人员 在医院范围（企业）的基础上进行调度。 二期将 发展 DOCS/Enterprise是一个解决大规模数据中心问题的软件应用程序。 工作人员 医院环境中的调度问题。 DOCS/Enterprise将在两个医疗中心进行Alpha测试 机构 验证设计和功能，以及三个额外的 机构 将参与可用性（Beta）测试。 第一阶段证明，DOCS算法非常适合大型 大小 医务人员的排班问题。 因为没有其他广告 软件 产品或任何已发布的算法的性能相比， 文件， 这是一个巨大的商业发展机会。 的 DOCS/Enterprise。 每家医院都会从这些员工身上受益 调度 系统 对于一家典型的医院来说，每年节省20万美元。

Medical facilities constantly face difficult staff scheduling problems. Every hospital and medical group will welcome a functional, computerized solution that actively optimizes scheduling. The DOCS algorithm - combining an accounting framework, constraints, and a Monte-Carlo stimulation - serves as a new methodology for optimal staff scheduling on a hospital-wide (enterprise) basis. Phase II will develop DOCS/Enterprise, a software application for solving large-scale staff scheduling problems in a hospital environment. DOCS/Enterprise will undergo Alpha testing at two medical institutions to verify the design and functionality and three additional institutions will participate in usability (Beta) testing. Phase I proved that the DOCS algorithm is well-suited for large size medical staff scheduling problems. Since no other commercial software products nor any published algorithms compare to the performance of DOCS, there is a significant commercial opportunity for the development of DOCS/Enterprise. Every hospital will benefit from this staff scheduling system. Savings are $200,000 per year for a typical hospital.