摘要
通过分析模具制造项目工期、费用与报酬的不确定性以及项目返修频繁发生的特点,建立了基于离散时间马尔可夫链的模具制造项目群随机演化模型,提出了基于MPICH2和并行Q学习的模型求解算法,在一定程度上克服了维数灾难问题。最后以Visual C＋＋6为工具,在多核环境下实现了该算法,并结合示例说明了算法的可行性与有效性。结果表明该算法在模具制造项目群随机调度中具有一定的应用价值。
Through the analysis of uncertainties of the durations,costs and rewards as well as the characteristic of frequent repairing in the mould and die manufacturing project,this paper proposed a stochastic evolution model of multiple mould and die manufacturing projects,which was on the basis of a discrete time Markov chain. With aim to overcome the curse of dimensionality,an algorithm based on MPICH2 and parallel Q-learning was put for ward to solve the above stochastic dynamic programming model. Finally,the algorithm was realized in a multi-core environment by using Visual C ＋＋ 6 and was explained with a sample example. The results show that the model is applicable and the algorithm is reliable and effective as well. And the results show that this algorithm can effectively solve stochastic scheduling problems for multiple mould and die manufacturing projects.
出处
《计算机应用研究》
CSCD
北大核心
2010年第9期3242-3246,共5页
Application Research of Computers
基金
国家“863”计划资助项目(2006AA04Z132)
国家自然科学基金资助项目(50875051)
广东工业大学青年基金资助项目(20062014)
