Flexible job shop scheduling system based on Petri network and improved genetic algorithm

Abstract

The invention discloses a flexible job shop scheduling system based on a Petri network and an improved genetic algorithm. The flexible job shop scheduling system is a system for minimizing completion time and power consumption according to peak-valley electricity price and indirect energy consumption, and comprises a job time selection module and a machine task assigning module, wherein the job time selection module is used for obtaining a migration activation time sequence FS and a migration processing sequence TS' by establishing an energy time Petri network model and a time selection simulation algorithm TSSA; the machine task assigning module is used for simulating by combination of improved genetic algorithm and the Petri network, finding out an optimal migration processing sequence TS, and obtaining a satisfactory solution of flexible job shop scheduling TI-FJSP. By adopting the flexible job shop scheduling system disclosed by the invention, making and implementation of a production plan can be effectively optimized, and a production mode with the lowest cost is provided for a company according to the peak-valley electricity price, so that the production cost of the company can be lowered, the utilization rate of energy can be increased, energy allocation can be optimized, resources can be saved, the environment can be protected, the economic benefits of the company can be optimized, and the industrial competitiveness of the company can be improved.

Description

technical field [0001] The invention relates to the technical field of flexible job shop scheduling, in particular to a flexible job shop scheduling system based on Petri net and improved genetic algorithm. Background technique [0002] At present, the improvement of energy utilization rate and the optimization of energy consumption of high-energy-consuming enterprises have become the main directions of consideration. Most manufacturing industries use electricity as the main energy consumption. Usually, electricity expenses account for more than 40% to 50% of product production costs. Enterprises are known as high-power-consuming enterprises, so many researchers have begun to focus on reducing carbon emissions and minimizing the production scheduling of the maximum completion time, which can not only achieve energy saving and emission reduction, but also save electricity costs and reduce production costs. [0003] The peak-off-peak electricity price (TOU) is a power price sy...

AI Technical Summary

Problems solved by technology

The production scheduling of enterprises has also expanded from simple process sequence arrangement to complex time selection. Process processing during the Pinggu electricity price period can significantly reduce electricity costs, but the time lag caused will increase indirect energy consumption and time costs

For a flexible manufacturing workshop, the differences in machine flexibility and energy efficiency further increase the complexity of scheduling, and the manufacturing workshop needs new production models and scheduling algorithms to balance electricity costs and time costs

In the production scheduling of the manufacturing industry, at present, most of the scheduling plans of high energy-consuming enterprises are based on minimizing the maximum completion time, considering the delay, and the lowest production cost as the scheduling goals, but usually ignore the consideration of peak-level and valley Scheduling of electricity pr

Images