Simulation-based optimization for strategic design problems

针对战略设计问题的基于仿真的优化

• 批准号: 249491-2007
• 负责人: Elhedhli, Samir
• 金额: $ 1.46万
• 依托单位: University of Waterloo
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2007
• 资助国家: 加拿大
• 起止时间: 2007-01-01 至 2008-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=366459
• 关键词: Simulation; based; optimization; strategic; design

We explore a novel approach to solve a variety of real-life strategic design problems that include logistics planning, call center staffing, inventory management, supply chain design, telecommunication network design, and airline scheduling. It is typical for these, and other realistic problems, that the stochastic nature of the process can not be captured using a known probability distribution function, or if this is possible the resulting performance measures do not have a closed form expression. These problems are characterized by a stochastic component that has to be taken into account at the strategic design stage, and are typically approached using stochastic programming and queuing theory. We explore another venue that imposes less restrictions on the type of distribution and setting of the stochastic component, leading to mathematical programs where some of the terms in the objective function or the constraints do not have a closed form expression and have to be evaluated using a simulation subroutine.The first step in the approach is to decompose the problem in a way that isolates the mathematical programming component in one subproblem and the simulation component in another. The two subproblems are coordinated using a master problem. As the subproblems are typically hard to solve (especially the simulation one), it is necessary to tackle the master problem using a method that converges quickly to a desirable solution. For that, the Analytic Center Cutting Plane Method (ACCPM) will be used.The application is part of a major research program to solve hard mathematical programming problems that arise in practice. The research program  combines mathematical programming and simulation to capture the complexities of such problems, without the need for  restrictive assumptions. It will  enable the training of graduate students in the modelling and solution of complex real-life problems that will hav a  direct impact on a number of industries.

我们探索了一种新的方法来解决各种现实生活中的战略设计问题，包括物流规划、呼叫中心人员配置、库存管理、供应链设计、电信网络设计和航空公司调度。对于这些和其他现实问题来说，过程的随机性质不能用已知的概率分布函数来捕捉，或者如果可能的话，结果的性能度量没有一个封闭的形式表达式。这些问题的特点是在策略设计阶段必须考虑到随机成分，并且通常使用随机规划和排队论来处理。我们探索了另一种对随机分量的分布类型和设置施加较少限制的场所，从而导致数学程序，其中目标函数或约束中的某些项没有封闭形式的表达式，必须使用模拟子程序进行评估。该方法的第一步是分解问题，将数学规划组件分离到一个子问题中，将模拟组件分离到另一个子问题中。这两个子问题使用一个主问题进行协调。由于子问题通常难以解决（特别是模拟问题），因此有必要使用一种快速收敛到理想解的方法来解决主问题。为此，将使用解析中心切割平面法（ACCPM）。该应用程序是一个主要研究项目的一部分，旨在解决在实践中出现的困难的数学规划问题。该研究计划结合了数学规划和模拟来捕捉这些问题的复杂性，而不需要限制性的假设。它将使研究生能够在模拟和解决复杂的现实问题方面得到培训，这些问题将对许多行业产生直接影响。