Abstract Motivated by the increasing demand of mass customisation in production systems, this paper proposes a robust and adaptive scheduling dispatching method for high-mix human-robot collaborative manufacturing facilities. Scheduling rules are derived to optimally track desired within mix, while handling uncertainty job processing times. The sequencing policy is dynamically adjusted online f...

To solve the two-workshop integrated scheduling problem with same device resources, existing algorithms pay attention to horizontal parallel processing of process tree and ignore tightness between vertical serial processes. A algorithm for production time-selective strategy Backtracking Strategy is proposed. The order each in needs be determined, which will completed by sequence sequencing stra...

Group sequencing is a well-studied scheduling method for the job shop problem. The goal of this method is to have a sequential flexibility during the execution of the schedule and to guarantee a minimal quality corresponding to the worst case. But the best case quality of a group sequence should also be interesting. This article presents a new method to evaluate the best-case quality. This meth...

We study the resource-constrained project scheduling problem with stochastic activity durations. We introduce a new class of scheduling policies for this problem, which make a number of a-priori sequencing decisions in a pre-processing phase, while the remaining decisions are made dynamically during project execution. The pre-processing decisions entail the addition of precedence constraints to...

Scheduling real-time tasks in a distributed-memory multiprocessor is characterized as sequencing a set of tasks and assigning them to processors of the architecture. Realtime systems research has extensively investigated the sequencing dimension of the scheduling problem by extending uni-processor scheduling techniques to more complex architectures. We introduce a technique that uses an assignm...

background and objectives: operating room (or) scheduling is key to optimal operating room productivity. the significant uncertainty associated with surgery duration renders scheduling of surgical operation a challenging task. this paper proposes a novel computational stochastic model to optimize scheduling of surgeries with uncertain durations. the model considers various surgical operation co...