Modeling and optimization method for production scheduling problem distribution set robust model

Abstract

The invention provides a modeling method for a production scheduling problem distribution set robust model, which belongs to the field of production scheduling and operations research. A distributed set robust optimization method based on an uncertain distribution function set is adopted to model the production scheduling problem, the model is composed of an objective function and constraint conditions, the objective of the model is to search for an optimal robust scheduling sequence, and thus, in a condition in which the total flow time of the sequence obeys the worst distribution in the processing time, the minimum condition risk value is realized. In the case of solution, the model is decomposed to an assignment subproblem and an integer two-order cone programming subproblem, and a minimum average processing time priority criterion and two Cauchy relaxation algorithms designed by the invention are adopted to optimize the model and obtain the optimal solution. The distribution set robust optimization method is applied to the production scheduling problem, the method is more applicable to the actual production condition compared with the existing robust modeling method, and in a condition of ensuring the system performance, a decision risk is reduced.

Description

technical field [0001] The invention belongs to the fields of production scheduling and operations research, and relates to a modeling and optimization solution method of a distributed set robust model of a production scheduling problem, which considers seeking a robust scheduling scheme with the least risk when the processing time of a workpiece is uncertain. Background technique [0002] The manufacturing industry occupies a very important position in the development of our country's national economy, and its development directly affects our country's comprehensive strength. Production scheduling is an important key technology in the manufacturing system, which aims to ensure that the manufacturing process is carried out efficiently and orderly. Designing a reasonable planning and scheduling strategy for the production process can effectively shorten the production cycle of products, increase the rate of on-time delivery, improve equipment utilization and reduce inventory....

AI Technical Summary

Problems solved by technology

3) This kind of stochastic model is usually NP-hard, and can only be solved by heuristic algorithm or dynamic programming algorithm. As the scale of the problem gradually expands, the difficulty of solving the stochastic scheduling model will increase exponentially

However, because only the boundary information of the variable range of uncertain parameters is used, and the system performance in the worst case is mainly considered, the decision obtained by this robust scheduling model based on the uncertainty set may be too conservative, sacrificing the parameter System performance under normal conditions

Images