A Logistics Network Optimization Method Based on Hybrid Automata

Abstract

The invention relates to a method for optimizing a logistics network based on a hybrid automaton. The method comprises the following steps: 1) constructing a hybrid automaton model of each device in a steel enterprise logistics network; 2) extending the hybrid automata model of each device to the entire Optimizing the scheduling process of iron and steel production logistics, constructing a hybrid automata model of the logistics network scheduling system of iron and steel enterprises; 3) using the graph search two-layer optimization algorithm to optimize the hybrid automata model of the logistics network scheduling system of iron and steel enterprises; 4) using the optimized The model optimizes the scheduling of the logistics network of iron and steel enterprises, and obtains the optimized scheduling scheme. Compared with the prior art, the present invention scientifically and rationally solves the coordination and optimization problem in the logistics network optimization, and is beneficial to realize the comprehensive benefit maximization of production profit and production characteristic performance.

Description

technical field [0001] The invention relates to the technical field of network optimization of raw material logistics enterprises of iron and steel enterprises, in particular to a logistics network optimization method based on a hybrid automaton. Background technique [0002] Raw materials for iron and steel enterprises mainly include iron ore powder, lump ore, and clean coal. Raw materials are mainly transported to the factory area by railway transportation, water transportation, etc., and belt transportation is mainly used among the main processes and storage facilities in the enterprise. The logistics process of raw materials among the production units of an iron and steel enterprise is as follows: figure 1 shown. Bulk raw materials such as iron ore powder, lump ore, and clean coal are affected by factors such as market supply fluctuations and transportation time fluctuations, which lead to obvious imbalances in the arrival of these raw materials in iron and steel enter...

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Problems solved by technology

[0003] The existence of bilinear item constraints and a large number of discrete variables makes the logistics problem a non-convex Mixed-Integer Nonlinear Programming (MINLP) problem. Due to its non-convex characteristics, the MINLP model is a class of difficult complex problems to solve

At the same time, due to the complexity of the logistics network optimization problem of iron and steel enterprises, it brings certain complexity to the modeling, and cannot solve the coordination and optimization problems in the logistics network optimization, which limits the comprehensive benefit maximization of production profits and production characteristics.

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