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

Utilizing available information on random machine breakdowns is highly effective in making
joint production and inspection decisions. The current paper studies the joint planning of …

This paper investigates a distributionally robust scheduling problem on identical parallel
machines, where job processing times are stochastic without any exact distributional form …

This paper studies a machine scheduling problem that minimizes the worst-case total
tardiness for unrelated parallel machines with sequence-dependent setup and uncertain …

Parallel machine scheduling is one of the most common studied problems in recent years,
however, this classic optimization problem has to achieve two conflicting objectives, ie …

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 investigate a stochastic distributed appointment assignment and scheduling problem,
which consists of assigning appointments to distributed service units and determining …

We study parallel machine scheduling for makespan minimization with uncertain job
processing times. To incorporate uncertainty and generate solutions that are, in some way …

Composite materials proved highly successful for aerospace applications in the last
decades, but increased cost pressure forces the composite industry to become more …

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 …