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不确定信息条件下的车间调度策略研究
引用本文:朱海平,邵新宇,张国军.不确定信息条件下的车间调度策略研究[J].计算机集成制造系统,2006,12(10):1637-1642.
作者姓名:朱海平  邵新宇  张国军
作者单位:华中科技大学,机械学院工业工程系,湖北,武汉,430074
基金项目:国家重点基础研究发展计划(973计划)
摘    要:为了在不确定的车间信息环境下做出正确的调度策略,提出了一种支持多目标和多优先级车间调度策略的随机规划模型,并给出了求解算法。该模型的求解通过包含3个步骤的混合智能算法来实现,首先利用随机仿真生成近似的样本数据,然后利用神经网络进行不确定目标和约束函数的逼近,并用遗传算法最终完成对多目标优化解的搜索。最后,通过一个汽车企业模具制造车间中调度问题的实例,验证了该模型和算法的有效性及实用性。

关 键 词:车间调度  随机规划  多目标优化  不确定信息
文章编号:1006-5911(2006)10-1637-06
修稿时间:2006年1月14日

Job-shop scheduling strategy under uncertain information environment
ZHU Hai-ping,SHAO Xin-yu,ZHANG Guo-jun.Job-shop scheduling strategy under uncertain information environment[J].Computer Integrated Manufacturing Systems,2006,12(10):1637-1642.
Authors:ZHU Hai-ping  SHAO Xin-yu  ZHANG Guo-jun
Abstract:To make the correct executive decision under uncertain job-shop information environment,a stochastic programming model supporting multi objective and multi priority for job-shop scheduling was proposed and a hybrid intelligent algorithm consisting of three steps was designed to solve this problem.Firstly,some approximate data samples were obtained by stochastic simulation.Secondly,a neural network model was constructed to approach the uncertain function of objectives and constraints.Then the genetic algorithm was used to search for the optimal solution.Finally,a case study of a scheduling problem in a job-shop for die manufacturing in a motor company was used to illustrate the feasibility and practicability of this model and algorithm.
Keywords:job-shop scheduling  stochastic programming  multi objective optimization  uncertain information
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