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建立了基于MTO-MTS的钢厂合同计划的整数规划模型,模型同时考虑库存余材匹配和生产计划,以提前/拖期惩罚、交货时间窗内拖后惩罚、生产费用、库存匹配费用、合同违约惩罚总额最小为目标.根据模型特点,构造了对非可行解进行启发式修复的改进粒子群算法求解策略.仿真实验首先对参数设置进行分析,然后对多组数据进行了结果分析,并在相同条件下,对比了本文模型与分阶段考虑库存匹配/合同计划方法的实验结果,验证了本文模型和算法的有效性.
An integer programming model of MTO-MTS-based contract planning was established. The model also considered the inventory residuals matching and production planning, with early / late punishment, delayed delivery within the time window, production costs, stock matching costs, And the minimum penalty of contract breach is the goal.According to the characteristics of the model, an improved Particle Swarm Optimization (PSO) algorithm for heuristic repair of non-feasible solutions is constructed.First, the parameter settings are analyzed and the results of multiple sets of data are analyzed Under the same conditions, the experimental results of the stock matching / contract planning method considering the model and the staged model are compared, and the validity of the proposed model and algorithm is verified.