This paper studies a distributed flowshop group robust scheduling problem with uncertain
processing times, which has great significance in actual production activities. First, we …

Recent research on distributionally robust (DR) machine scheduling has used a variety of
approaches to describe the region of ambiguity of uncertain processing times by imposing …

Stochastic scheduling has received much attention from both industry and academia.
Existing works usually focus on random job processing times. However, the uncertainty …

In the traditional single-machine scheduling problem with uncertain processing time,
distributionally robust optimization models are established in situations where the …

In the present study, a single machine scheduling problem with job release dates is
considered, where the job processing time is depicted by an ambiguity set, with the mean …

The β-robust machine scheduling has attracted increasing attention as an effective method
to hedge against uncertainty. However, existing β-robust scheduling models rely on the …

We develop a distributionally robust optimisation (DRO) model based on a risk measure for
the parallel machine scheduling problem (PMSP) with random job processing times. We …

This paper proposes an interesting variant of the parallel machine scheduling problem with
sequence-dependent setup times, where a subset of jobs has to be selected to guarantee a …

A parallel-machine scheduling problem with preventive maintenance is studied in the paper.
Because of the existence of indeterminacy phenomenon, the processing and maintenance …

We consider a stochastic parallel machine scheduling problem, where the jobs have
uncertain processing time described by a normal probability distribution. The objective is to …