This paper addresses the single-machine scheduling problem with release times minimizing the total completion time. Under the circumstance of incomplete global information at each decision time, a two-level rolling scheduling strategy (TRSS) is presented to create the global schedule step by step. The estimated global schedules are established based on a dummy schedule of unknown jobs. The first level is the preliminary scheduling based on the predictive window and the second level is the local scheduling for sub-problems based on the rolling window. Performance analysis demonstrates that TRSS can improve the global schedules. Computational results show that the solution quality of TRSS outperforms that of the existing rolling procedure in most cases.
A new bottleneck-based heuristic for large-scale flow-shop scheduling problems with a bottleneck is proposed, which is simpler but more tailored than the shifting bottleneck （SB） procedure. In this algorithm, a schedule for the bottleneck machine is first constructed optimally and then the non-bottleneck machines are scheduled around the bottleneck schedule by some effective dispatching rules. Computational results show that the modified bottleneck-based procedure can achieve a tradeoff between solution quality and computational time comparing with SB procedure for medium-size problems. Furthermore it can obtain a good solution in quite short time for large-scale scheduling problems.
This paper discusses the single-machine rescheduling problem with efficiency and stability as criteria, where more than one disruption arises in large-scale dynamic circumstances. Partial rescheduling (PR) strategy is adopted after each disruption and a rolling mechanism is driven by events in response to disruptions. Two kinds of objective functions are designed respectively for PR sub-problem involving in the interim and the terminal of unfinished jobs. The analytical result demonstrates that each local objective is consistent with the global one. Extensive computational experiment was performed and the computational results show that the rolling PR strategy with dual objectives can greatly improve schedule stability with little sacrifice in efficiency and provide a reasonable trade-off between solution quality and computational efforts.
Active schedule is one of the most basic and popular concepts in production scheduling research. For identical parallel machine scheduling with jobs＇ dynamic arrivals, the tight performance bounds of active schedules under the measurement of four popular objectives are respectively given in this paper. Similar analysis method and conclusions can be generalized to static identical parallel machine and single machine scheduling problem.
