柔性自动化车间的最优随机生产计划

摘要

The paper addresses the problem of the optimal stochastic production planning in flexible automation workshops(FAW),each with a number of flexible manufacturing systems (FMS). A stochastic nonlinear programming model of production planning in a workshop is built up and then transformed into a deterministic nonlinear programming model and further into a linear programming model by adding constraints. Because the scale of the model for a general workshop is too large to be solved in simplex method on a microcomputer within acceptable time, a Karmarkar's algorithm and an interaction/prediction algorithm are used to solve the model, on the basis of which the corresponding programs have been written.Through production planning examples,the Karmarkar's algorithm,interaction/prediction algorithm and linear programming method in Matlab are compared, thus showing that the proposed approaches are very suitable for decomposing optimally FAW's product demand plans into short-term stochastic plans to be executed by FMS in FAW.%研究了由多个柔性制造系统组成的柔性自动化车间的最优随机生产计划问题。首先根据实际需要建立车间生产计划的随机非线性规划模型。为求解方便，将其近似转化成确定非线性规划模型，并通过引进约束进一步转化成线性规划模型。由于这种模型规模较大，很难在微机上用单纯形法在可接受的时间内获得其最优解。为此，分别用卡马卡算法和基于卡马卡算法的关联预测法，求解柔性自动化车间最优生产计划问题，并编制了相应软件。最后通过算例研究，比较了卡马卡算法、基于卡马卡算法的关联预测法和Matlab中的线性规划法，结果表明，所提方法非常适合将不确定性环境中的随机产品需求计划，最优分解成由柔性自动化车间中各柔性制造系统执行的短期随机计划。