Optimum Scheduling Under Batch Failure Scenario

Optimum workforce scheduling under the (14, 21) days-off timetable

An efficient optimum solution is presented for a real-life employee daysoff scheduling problem with a three-week cycle. Over a given work cycle, each worker is given 14 successive workdays and 7 successive off days. This three-week days-off timetable is referred to as the (14, 21) schedule. Given different labor demands for each day of the week, the primary objective is to minimize the number o...

Complexity of single machine scheduling problems under scenario-based uncertainty

We consider scheduling environments where some job characteristics are uncertain. This uncertainty is modeled through a finite set of well-defined scenarios. In such a context, we search for a solution that is acceptable for any considered scenario. For this purpose, several criteria can be applied to select among solutions. We use here the so-called absolute robustness criterion. We present al...

Data - Driven Batch Scheduling

Parallel Machine Batch Scheduling

The problem of scheduling G groups of jobs on m unrelated parallel machines is considered. Each group consists of several identical jobs. Implicit in a schedule is a partition of a group into batches; all jobs of a batch are processed jointly. It is possible for diierent batches of the same group to be processed concurrently on diierent machines. However, at any time, a batch can be processed o...

Batch Scheduling in Flexible Flow Shop

In this paper, the problem of batch scheduling in a flexible flow shop environment is studied. It is assumed that machines in some stages are able to process a number of jobs simultaneously. The applications of this problem can be found in various industries including spring and wire manufacturing and in auto industry. A mixed integer programming formulation of the problem is presented and it i...