会员体验
专利管家(专利管理)
工作空间(专利管理)
风险监控(情报监控)
数据分析(专利分析)
侵权分析(诉讼无效)
联系我们
交流群
官方交流:
QQ群: 891211   
微信请扫码    >>>
现在联系顾问~
热词
    • 2. 发明授权
    • Method and apparatus for discrete activity resourse allocation through
cardinality constraint generation
    • 通过基数约束产生离散活动资源分配的方法和装置
    • US5216593A
    • 1993-06-01
    • US645385
    • 1991-01-24
    • Brenda L. DietrichLaureano F. Escudero
    • Brenda L. DietrichLaureano F. Escudero
    • B65G61/00G06F19/00G06Q10/06G06Q10/08
    • G06Q10/06G06Q10/0875
    • The required computational effort in the areas of production planning and logistics, scheduling, distribution and resource allocation is reduced by a procedure for solving a Discrete Activity Resource Allocation (DARA) problem. The procedure begins by reducing all activities and resources which do not contribute to maximizing benefit. Thus, all infeasible and non-profitable activities are discarded and all non-constraining resources are discarded, thereby considerably simplifying the solution to the problem. Next, an automatic mathematical model formulation of the DARA problem is performed. Based on this model, a list of cliques and covers are generated. The linear relaxation of the DARA problem using standard linear programming software is solved, and the generated list of clique and cover induced inequalities is scanned to select a set violated by the solution of the linear relaxation of the DARA problem. For those inequalities found, constraints are appended to the formulated DARA problem, forming another DARA problem with the same set of variables, but with additional constraints. The new DARA problem is then solved using the previous solution as the start of the solution. Based on this solution, the generated list of clique and cover induced inequalities is again scanned, and this process is continued until no violated inequalities are found. At this point in the procedure, conventional branch-and-bound or branch-and-cut routines are used to solve the enlarged DARA problem. The solution yields the optimal resource allocation producing the maximum benefit.
    • 通过解决离散活动资源分配(DARA)问题的过程,减少了生产计划和物流,调度,分配和资源分配领域所需的计算量。 程序开始于减少所有不利于最大化利益的活动和资源。 因此,所有不可行和非盈利的活动都被丢弃,所有非限制性资源被丢弃,从而大大简化了解决问题的方法。 接下来,执行DARA问题的自动数学模型公式。 基于此模型,生成了一个集合和封面的列表。 解决了使用标准线性规划软件的DARA问题的线性弛豫,并且扫描了产生的集团和覆盖引起的不等式列表,以选择通过DARA问题的线性弛豫解决方案违反的集合。 对于发现的这些不等式,约束被附加到DARA问题的解决之中,形成另一个DARA问题,同一组变量,但有额外的约束。 然后使用先前的解决方案作为解决方案的开始,解决新的DARA问题。 基于此解决方案,再次扫描了所产生的集团和覆盖引起的不平等的列表,并且继续这一过程,直到没有发现违反不等式。 在该过程的这一点上,常规的分支和分支和切割例程被用于解决扩大的DARA问题。 该解决方案产生最佳的资源配置,产生最大的收益。
    • 7. 发明授权
    • Optimization of manufacturing resource planning
    • 优化制造资源规划
    • US5630070A
    • 1997-05-13
    • US108014
    • 1993-08-16
    • Brenda L. DietrichRobert J. Wittrock
    • Brenda L. DietrichRobert J. Wittrock
    • G05B19/418B65G61/00G06F19/00G06Q10/06G06F17/60
    • G06Q10/06G06Q10/0631G06Q10/06313G06Q10/06315G06Q10/06375Y02P90/20
    • A method for constrained material requirements planning, optimal resource allocation, and production planning provides for an optimization of a manufacturing process by designating the amounts of various manufactured products to be produced, which products include both end products as well as subassemblies to be employed in the manufacture of one or more of the end products. In order to accomplish the optimization, the method employs an objective function such as the maximization of income in a situation wherein there are limitations on the inventory of raw materials and tools to be employed in the manufacturing process. Data describing elemental steps in the manufacturing process for the production of each end product, as well as the quantity or demand for each end product which is to be supplied, are presented as a set of linear mathematical relationships in matrix form to be inserted in a computer which determines the optimum number of each end product in accordance with an LP optimization algorithm. The matrix contains bill of material data, and various constraints such as a constraint on the sum of products shipped and used as subassemblies, and constraints based on inventory, on available time for use of resources such as tools, and on inventory left over from an early production run for a later run.
    • 用于约束材料需求计划,最佳资源分配和生产计划的方法通过指定要生产的各种制成品的数量来优化制造过程,哪些产品包括要在其中使用的最终产品以及子组件 制造一种或多种最终产品。 为了完成优化,该方法采用目标函数,例如在制造过程中要采用的原材料库存和工具存在限制的情况下收入最大化。 描述用于生产每个最终产品的制造过程中的元素步骤的数据以及要提供的每个最终产品的数量或需求被呈现为矩阵形式的一组线性数学关系,以插入到 计算机,其根据LP优化算法确定每个最终产品的最佳数量。 该矩阵包含物料清单数据,以及各种约束,例如对运送和用作子组件的产品的总和的限制,以及基于库存的限制,使用诸如工具的资源的可用时间以及从 早期生产运行后续运行。