Hybrid intelligent scheduling optimization method of manufacturing enterprise workshop

Abstract

The invention discloses a hybrid intelligent scheduling optimization method of a manufacturing enterprise workshop. The method comprises the following steps of: initializing related parameters of an HS algorithm and an SA algorithm; according to different production tasks, inputting processing information relating to each task; using a coding mode based on working procedures to code questions, and then utilizing a random generation mode to generate harmony memory HM initial solutions; utilizing the SA algorithm to carry out neighborhood transformation on all the initial solutions, if the solutions after the transformation are better than the initial solutions, then receiving the solutions after the transformation; and if not, then receiving the solutions after the transformation with a probability which successively decreases with a temperature in the SA algorithm; utilizing three kinds of mechanism, such as harmony memory learning, variable fine tuning and new tone random generation, to generate new solutions; utilizing the SA algorithm to carry out neighborhood transformation on the new solutions and to determine whether to receive the new solutions; establishing a target optimization function, and updating the HM according to an optimization result; and if a maximum iteration number is reached, outputting an optimal harmony solution, and drawing a scheduling Gantt chart of the system. The hybrid intelligent scheduling optimization method has the advantages that the hardware requirements are low, and the optimal solution can be found easily.

Description

technical field [0001] The invention relates to the technical field of workshop job scheduling, in particular to a hybrid intelligent scheduling optimization method for a manufacturing enterprise workshop. Background technique [0002] A manufacturing enterprise workshop system is a manufacturing system that includes multiple production tasks and multiple available resources (machines). The hybrid intelligent scheduling optimization of the system is a process of automatically finding the optimal task scheduling method by integrating multiple intelligent optimization algorithms according to the different production tasks and available resources. The task scheduling sequence obtained by using job scheduling optimization can improve equipment utilization, shorten production cycle, increase production flexibility, and ultimately reduce enterprise production costs, reduce production energy consumption and improve enterprise economic benefits. [0003] In order to seek a better w...

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Problems solved by technology

However, the core module of job shop scheduling in patent CN101303749A—the decision module uses a second-order optimized genetic algorithm. Although it solves the system bottleneck problem in the job shop scheduling problem, it requires a large amount of storage space to save Individual information, high hardware requirements, and the calculation process takes a lot of time

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