基于遗传算法的多工序多机器调度优化研究

随着人民生活质量的提高,消费者对定制化生产提出了更高的要求,此外,在新的经济环境下,降本增效对于提升制造企业的发展能力具有重要的意义,基于此,本文提出了基于遗传算法的多工序多机器调度优化研究。首先,设计了基于完工时间最小化的多工序多机器加工约束的生产调度优化模型;其次,采用遗传算法设计了求解上述生产调度优化模型的算法;最后,通过案例验证了本文构建的优化模型及设计的优化算法,并绘制了以最小化完工时间为优化目标的生产调度甘特图。研究结果表明,本文构建的模型及设计的算法具有一定的实用性,可指导企业制定较优的生产调度方案。

Research on Multi-process and Multi-machine Scheduling Optimization Based on Genetic Algorithms

With the improvement of people’s living quality, consumers put forward higher requirements for customized production. In addition, in the new economic environment, reducing costs and increasing efficiency is of great significance to enhance the development ability of manufacturing enterprises. Based on this, this paper proposes a multi-process and multi-machine Scheduling Optimization Research Based on genetic algorithm. Firstly, a production scheduling optimization model with multi-process and multi-machine constraints based on minimum completion time is designed;secondly, the genetic algorithm is used to design the algorithm for solving the above production scheduling optimization model;finally, the optimization model and the optimization algorithm designed in this paper are verified by a case study, and the production scheduling Gantt with the objective of minimizing completion time is drawn. Graph. The results show that the model and algorithm constructed in this paper have certain practicability and can guide enterprises to formulate better production scheduling schemes.