Single-machine minimized total tardiness scheduling method based on distributed robust model

Abstract

The invention provides a single-machine minimized total tardiness scheduling method based on a distributed robust model and belongs to the technical field of production scheduling and internal and external production resource optimization. The method comprises the steps that a distributed robust optimization model for solving the single-machine scheduling problem is established firstly to obtain atarget function expression of the model; then, the distributed robust optimization model is converted into an integer second-order cone programming model; the converted model is solved, arrangement combinations of all workpiece machining sequences are expressed in a search tree in an enumeration way, the search tree is pruned through a branch-and-bound algorithm, and finally an optimal single-machine scheduling scheme of the minimized total tardiness is obtained. The method gives consideration to uncertain factors of a production environment, so that the model is a determined single-machine model more conforming to the actual production situation compared with an assumed production environment, and the obtained scheduling scheme can be better applied to actual production.

Description

technical field [0001] The invention belongs to the technical field of production scheduling and optimization of production internal and external resources, and particularly relates to a single-machine scheduling method based on a distributed robust model that minimizes total delay in the case of uncertain processing time. Background technique [0002] The production scheduling problem is an indispensable key problem in the manufacturing and service industries. It aims to shorten the manufacturing cycle, reduce production costs, and improve equipment utilization through rational allocation and optimization of internal and external resources. It is of great significance to many enterprises. Therefore, production scheduling has naturally become the core content of common concerns of various advanced manufacturing models. With the introduction of concepts such as agile manufacturing and intelligent manufacturing, people's demand for punctual product delivery has become increasi...

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Problems solved by technology

However, using the fluctuation range of parameters to describe uncertain parameters, and then using traditional robust optimization methods to optimize, the results obtained are often too conservative, because this method usually only considers the extreme cases of uncertain parameters, that is, the interval Two endpoints, and in the actual production process, the probability of this situation is very small, so the solution obtained for the extreme situation will often lose a lot of performance due to the consideration of robustness

In terms of practical applications, there are no examples of applying distributed robust optimization methods to the single-machine scheduling problem of minimizing total delay

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