Global optimization preprocessing method for intelligent manufacturing production scheduling

A technology for production scheduling and global optimization, applied in manufacturing computing systems, data processing applications, forecasting, etc., to achieve the effect of strengthening slack sub-problems, reducing the difficulty of optimization, and simplifying problems

Inactive Publication Date: 2020-02-21
苏州圣典企业管理咨询有限公司
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  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

[0007] Purpose of the invention: In order to overcome the above deficiencies, the purpose of the present invention is to provide a global optimization preprocessing method for intelligent manufacturing production scheduling. On the premise of ensuring the global optimum, a pre-solution algorithm is used for mixed integer linear programming problems, and for mixed integer For nonlinear programming problems, first deduce the optimality conditions of mixed integer nonlinear programming problems, and apply them in the search domain reduction, which effectively improves the solution performance, and can directly act on engineering decision-making problems with complex structures, greatly improving Real-time and solution quality of complex production scheduling decisions

Method used

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Embodiment 1

[0038] Presolver for mixed integer linear programming problems

[0039] Including the following steps:

[0040](1) Variable selection based on the Fourier-Motzkin elimination method: estimate the number of non-zero elements of the model after the Fourier-Motzkin elimination method is executed, apply the Fourier-Motzkin elimination method to eliminate variables and reduce non-zero elements, and reduce the number of non-zero elements according to the , to sort the variables, and the higher the number of cuts, the higher the priority of the variable;

[0041] (2) Redundant constraint elimination method based on Fourier-Motzkin elimination method: After eliminating selected variables based on Fourier-Motzkin elimination method, the constraint redundancy is judged through boundary reasoning. If the upper and lower bounds of the reasoning conflict or violate If the original constraint boundary is used, it can be directly determined that the original linear programming problem is no...

Embodiment 2

[0047] Search Domain Reduction for Mixed Integer Nonlinear Programming Problems

[0048] Including the following steps:

[0049] (1) Deriving optimality conditions: deriving optimality conditions through the monotonic characteristics of the objective function and constraints;

[0050] (2) Search domain reduction: through the above optimality conditions, as a set of constraints that the optimal solution must satisfy, and filter the solution domain that satisfies these constraints, and use it as the reduced search domain; the search domain reduction includes outputting Single-constraint search domain reduction, multi-constraint search domain reduction;

[0051] The narrowing of the search domain includes the following steps:

[0052] 1) Select a variable, calculate the gradient boundary of the objective function and constraints for the variable in a forward direction, and if the gradient boundary obtained by the forward calculation meets the optimality condition, the algorithm...

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Abstract

The invention discloses a global optimization preprocessing method for intelligent manufacturing production scheduling. The global optimization preprocessing method comprises the following steps: pre-solving a mixed integer linear programming problem, and reducing a search domain for the mixed integer nonlinear programming problem; the pre-solving of the mixed integer linear programming problem comprising the following steps: (1) performing variable selection based on a Fourier-Motzkin elimination method; (2) performing a redundancy constraint elimination method based on a Fourier-Motzkin elimination method; and (3) pre-solving a linear programming problem based on a Fourier-Motzkin elimination method. According to the global optimization preprocessing method for intelligent manufacturingproduction scheduling, aiming at solving the problem of solving a large-scale engineering decision optimization problem in practice, two types of model preprocessing methods with universality are adopted, so that the solving performance is effectively improved, the method can be directly applied to engineering decision problems with complex structures, and the real-time performance and the qualityof complex production scheduling decisions are greatly improved.

Description

technical field [0001] The invention belongs to the technical field of intelligent manufacturing, and in particular relates to a global optimization preprocessing method for intelligent manufacturing production scheduling. Background technique [0002] In the context of the transformation of many enterprises towards intelligent manufacturing, manufacturing industry informatization, physical resource virtualization, production process intelligence, and industrial resource service have become popular research topics and engineering propositions. At the same time, the transformation of the manufacturing industry with the integration of informatization and industrialization as the mainstream is unfolding in all directions. The core issue is how to organically integrate advanced technologies and realize the high integration of resources, services and production management, so as to realize the transformation and upgrading of production models. [0003] In the current transformati...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F17/11G06Q10/04G06Q50/04
CPCG06F17/11G06Q10/04G06Q50/04Y02P90/30
Inventor 韩继利
Owner 苏州圣典企业管理咨询有限公司
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