基于状态集分解的一类车间计划、调度算法

Integration of Planning and Scheduling Problem Based on States Decomposition

针对集成生产计划、调度中的一类强NP-hard问题,提出了基于状态集分解的分层混合优化算法。通过状态集分解将计划、调度一体化模型转化为一系列的最小网络流模型,上层搜索通过建立可行性必要条件和启发式规则,迅速排除劣解或不可行解,缩小搜索范围。底层搜索主要依靠网络流算法及对偶再优化算法,辅以启发式策略,做小范围的局部精确寻优。数据仿真说明了算法的有效性。

A novel hybrid algorithm based on states decomposition with hierarchical search was proposed to address the simultaneously planning and scheduling problem arising in industry which was proven to be strong NP-hard. The problem was first transformed into a series of network flow models by states decomposition. The top level inferior or infeasible solutions were precluded quickly through feasibility checking and problem-specific strategies which greatly reduced the searching area. The network flow algorithm and the dual re-optimization algorithm incorporated with local search methods were employed to resolve the remaining problem at the lower level. The computational experiments demonstrate the efficiency of the proposed algorithm.