公开(公告)号：US08412551B2

公开(公告)日：2013-04-02

申请号：US10970201

申请日：2004-10-21

申请人： Xiaoming Feng ,  Yuan Liao ,  John Dennis Finney ,  Adolfo Fonseca

发明人： Xiaoming Feng ,  Yuan Liao ,  John Dennis Finney ,  Adolfo Fonseca

IPC分类号： G06Q10/00

CPC分类号： G06Q10/04 ,  G06Q10/06314

摘要： A method and computer program product for optimization of large scale resource scheduling problems. Large scale resource scheduling problems are computationally very hard and extremely time consuming to solve. This invention provides a Lagrangian relaxation based solution method. The method has two distinct characteristics. First, the method is formal. It is completely structure-based and does not use any problem domain specific knowledge in the solution process, either in the dual optimization or the primal feasibility enforcement process. Second, updating the Lagrangian multipliers after solution of every sub-problem without using penalty factors results in fast and smooth convergence in the dual optimization. The combination of high quality dual solution and the structure-based primal feasibility enforcement produces a high quality primal solution with very small solution gap. An optimal solution is first found to the dual of the resource scheduling problem by sequentially finding a solution to a plurality of sub-problems and updating a set of values used in the dual problem formulation after each sub-problem solution is obtained. Coupling constraint violations are systematically reduced and the set of values are updated until a feasible solution to the primal resource scheduling problem is obtained. An initial set of multiplier values is further determined by solving a relaxed version of the primal problem where most of the local constraints except the variable bounds are relaxed.

摘要翻译： 一种用于优化大规模资源调度问题的方法和计算机程序产品。 大规模的资源调度问题在计算上非常困难，非常耗时。 本发明提供了一种基于拉格朗日弛豫解的方法。 该方法有两个不同的特征。 首先，方法是正式的。 它是完全基于结构的，并且在解决过程中不使用任何问题领域特定的知识，无论是在双重优化还是初始可行性执行过程中。 其次，在不使用罚分因子的情况下，在解决每个子问题之后更新拉格朗日乘数导致双重优化中的快速平滑收敛。 高质量的双重解决方案与基于结构的初始可行性执行相结合，产生了具有非常小的解决方案差距的高质量原始解决方案。 首先通过在获得每个子问题解决方案之后顺序找到多个子问题的解决方案和更新在双问题公式中使用的值的集合，首先找到了资源调度问题的双重优化解决方案。 系统地减少耦合约束违规，并且更新值集合，直到获得对原始资源调度问题的可行解。 通过解决原始问题的松弛版本进一步确定初始的乘数值集，其中大部分局部约束除了可变边界之外都被放宽。

公开(公告)号：US20060089864A1

公开(公告)日：2006-04-27

申请号：US10970201

申请日：2004-10-21

申请人： Xiaoming Feng ,  Yuan Liao ,  John Dennis Finney ,  Adolfo Fonseca

发明人： Xiaoming Feng ,  Yuan Liao ,  John Dennis Finney ,  Adolfo Fonseca

IPC分类号： G06F17/60

CPC分类号： G06Q10/04 ,  G06Q10/06314

摘要： A method and computer program product for optimization of large scale resource scheduling problems. Large scale resource scheduling problems are computationally very hard and extremely time consuming to solve. This invention provides a Lagrangian relaxation based solution method. The method has two distinct characteristics. First, the method is formal. It is completely structure-based and does not use any problem domain specific knowledge in the solution process, either in the dual optimization or the primal feasibility enforcement process. Second, updating the Lagrangian multipliers after solution of every sub-problem without using penalty factors results in fast and smooth convergence in the dual optimization. The combination of high quality dual solution and the structure-based primal feasibility enforcement produces a high quality primal solution with very small solution gap. An optimal solution is first found to the dual of the resource scheduling problem by sequentially finding a solution to a plurality of sub-problems and updating a set of values used in the dual problem formulation after each sub-problem solution is obtained. Coupling constraint violations are systematically reduced and the set of values are updated until a feasible solution to the primal resource scheduling problem is obtained. An initial set of multiplier values is further determined by solving a relaxed version of the primal problem where most of the local constraints except the variable bounds are relaxed.

摘要翻译： 一种用于优化大规模资源调度问题的方法和计算机程序产品。 大规模的资源调度问题在计算上非常困难，非常耗时。 本发明提供了一种基于拉格朗日弛豫解的方法。 该方法有两个不同的特征。 首先，方法是正式的。 它是完全基于结构的，并且在解决过程中不使用任何问题领域特定的知识，无论是在双重优化还是初始可行性执行过程中。 其次，在不使用罚分因子的情况下，在解决每个子问题之后更新拉格朗日乘数导致双重优化中的快速平滑收敛。 高质量的双重解决方案与基于结构的初始可行性执行相结合，产生了具有非常小的解决方案差距的高质量原始解决方案。 首先通过在获得每个子问题解决方案之后顺序找到多个子问题的解决方案和更新在双问题公式中使用的值的集合，首先找到了资源调度问题的双重优化解决方案。 系统地减少耦合约束违规，并且更新值集合，直到获得对原始资源调度问题的可行解。 通过解决原始问题的松弛版本进一步确定初始的乘数值集，其中大部分局部约束除了可变边界之外都被放宽。