Solution algorithms for the number of tardy jobs minimisation scheduling with a time-dependent learning effect
研究单机调度中考虑时间依赖学习效应时，如何安排工序顺序使拖期工件数最少，提出了两种启发式算法和分支定界算法，实验表明分支定界可解18个工件以内的问题，启发式算法MFLA高效有效。
This paper deals with a single-machine scheduling problem with a time-dependent learning effect. The goal is to determine the job sequence that minimise the number of tardy jobs. Two dominance properties, two heuristic algorithms and a lower bound to speed up the search process of the branch-and-bound algorithm are proposed. Computational experiments show that the branch-and-bound algorithm can solve instances up to 18 jobs in a reasonable amount of time, and the proposed heuristic algorithm MFLA performs effectively and efficiently