基于NSGA-II算法的柔性流水车间优化调度模型的构建与应用

Construction andApplication of A Flexible Flow-shop Optimization Scheduling Model Based on NSGA-II Algorithm

中文关键词:  多目标优化  流水车间  NSGA-II  生产调度

Key Words:multi-objective optimization  flow-shop  NSGA-II  production scheduling

中文摘要:

      为解决造纸企业的高效优化排产问题，使机器利用率最高、减少产品切换次数以及满足客户对产品的时间需求，构建了以成本及最大完工时间最小化为优化目标的两阶段柔性流水车间调度优化模型，并通过一种快速非支配遗传算法（NSGA-II）来求解该模型。结果表明，与人工排产相比，NSGA-II得到的排产结果缩短了约6.5%的最大完工时间，降低了约4.7%的生产成本。

Abstract:

      In order to solve the problem of efficient optimized production scheduling in papermaking enterprises， the machine operation rate should be the highest， the product switching times， and the time of supplying products should be met the requirement of customer. A two-stage flexible flow-shop scheduling optimization model with cost minimization and make span minimization as optimization objectives was constructed and a fast non-dominated genetic algorithm （NSGA-II） was used to solve the model. The results showed that compared with manual production scheduling， the production scheduling results obtained by NSGA-II shorten the makespan by about 6.5% and reduce the production cost by about 4.7%.