基于遗传算法的多资源平衡工序排序优化决策

工序排序是生产管理中经常遇到的问题,多资源平衡工序优化是提高生产效率、降低生产成本的重要手段,至今尚未见十分有效的解法。本文建立了典型的网络计划多资源平衡工序优化的数学模型,以每道工序开工时间作为设计变量,极小化某种关键性资源需求的最大量或波动的幅度,并运用所设计的改进遗传算法对该模型进行了求解,获得了多组最优工序计划。这就使得生产调度安排灵活机动,便于智能调度。

Optimal Decision of Multi-resource Balance Operation Sequencing by Using Genetic Algorithm

Operation sequencing is an issue that is often encountered in production management. The multi-resource balance operation sequencing optimization is an important means to increase production efficiency and to reduce the production costs, which has not been solved perfectly. The optimization mathematical model of multi-resource balance operation sequencing for typical network plans is proposed in the paper, in which the starting times of variable operations are selected to be variables and maximum or standard deviation of a key resource is the objective function to be minimized. The improved genetic algorithm is employed to solve for the several operation sequencings with same minimum of the objective function, which implies that production operation sequencing be not unique and can be arranged flexibly.