A logistics vehicle scheduling area optimization method for a mixed model assembly line with an uncertain demand

Abstract

The invention relates to a logistics vehicle scheduling area optimization method for a mixed model assembly line with an uncertain demand, and is used to obtain a region division program of logisticsdistribution in a mixed model assembly line. The method comprises the following steps of: 1) defining the full load ratio of logistics distribution vehicles and the complexity of distribution tasks; 2) obtaining the constraint conditions of a multi-objective optimization model, and establishing a multi-objective optimization model with a goal of maximization of the average full load ratio of the logistics distribution vehicles and minimization of complexity indexes of the distribution tasks; and 3) using a genetic algorithm to solve the multi-objective optimization model to obtain an optimal allocation program. Compared with the methods in the prior art, the method in the invention has the advantages of ensuring the full load ratio of the delivery vehicles, reducing the complexity of the delivery tasks, avoiding the unstable state of the delivery vehicles caused by the accumulation of the demand uncertainty factors and improving the robustness of the logistics scheduling of the mixed model assembly line.

Description

technical field [0001] The invention relates to the technical field of automated production lines, in particular to a method for optimizing logistics vehicle scheduling areas of mixed-flow production lines with uncertain demand. Background technique [0002] With the increase of diversified demand in the market, the requirements for products have changed from the previous single-variety large batches to multi-variety small batches. Therefore, more and more manufacturing companies choose flexible production lines capable of multi-variety mixed production to quickly respond to the market. In particular, enterprises that focus on assembly production, such as automobile, computer and toy manufacturing industries, need an assembly line capable of multi-variety mixed assembly, that is, Mixed Model Assembly. The mixed-flow assembly line can assemble different deformed products in real time according to market needs. [0003] According to statistics, in the manufacturing process, ...

AI Technical Summary

Problems solved by technology

However, in actual work, the acquisition of information is not timely or complete

For example, temporary insertion of orders and changes in the delivery date will affect the market demand. If the production scheduling cannot adapt to the fluctuating demand of the market, the production tasks cannot be completed on time, resulting in losses for the enterprise.

At present, in the mixed-flow manufacturing industry, the implementation of material distribution management is not strong enough, and the real-time control ability is generally weak, so that material distribution cannot work as expected, and the production situation is not stable enough

Images