提出一种求解机组组合(unit commitment,UC)问题的改进优先顺序法.利用机组的最小平均煤耗成本,建立UC问题一个新的整数线性规划模型(integer linear programming,ILP),从而将UC问题分解为一个仅含0、1变量的ILP问题和一个二次规划问题,减小了UC问题的规模和求解难度.利用ILP连续松弛问题的最优解,提出一种求解UC问题的改进优先顺序法.数值结果表明,所建ILP模型合理有效,所提方法具有良好的收敛性,和其他优先顺序法相比,获得了更好的数值结果.
提出一种求解安全约束机组组合(security constrained unit commitment,SCUC)问题的邻域搜索外逼近(outer approximation based on neighborhood search,NS-OA)法. OA将SCUC问题分解为一系列混合整数线性规划(mixed integer linear programming,MILP)主问题和非线性规划(nonlinear programming,NLP)子问题,通过MILP主问题和NLP子问题的最优解来逼近SCUC问题的最优解.为克服迭代过程中MILP主问题规模大的不足,利用SCUC问题对应UC问题的最优解为中心来构造邻域,然后在此邻域内搜索MILP主问题的最优解.数值结果表明,所提邻域搜索能有效减小搜索空间,大大提高了算法的计算效率,所提NS-OA算法能有效求解大规模SCUC问题,具有良好的应用前景.
In the rescheduling on a single machine, a set of the original jobs has already been scheduled, in order to make a given objective function is optimal. The decision maker needs to insert the new jobs into the existing schedule without excessively disrupting it. A batching machine is a machine that can handle up to some jobs simultaneously. In this paper,we consider the total completion time under a limit on the sequence disruptions for parallel batching based on rescheduling. For the parallel batching problem based on rescheduling, we research the properties of feasible schedules and optimal schedules on the total completion time under a limit on the maximum time disruptions or total time disruptions, in which the jobs are sequenced in SPT order, and give out the pseudo-polynomial time algorithms on the number of jobs and the processing time of jobs by applying the dynamic programming method.
