We introduce a new class of distributionally robust optimization problems under decision-
dependent ambiguity sets. In particular, as our ambiguity sets, we consider balls centered on …

Unrelated parallel machine scheduling problem (UPM) is widely studied in the scheduling
literature because of its extensive application area in the industry. Since it has a stochastic …

We apply logic-based Benders decomposition (LBBD) to two-stage stochastic planning and
scheduling problems in which the second stage is a scheduling task. We solve the master …

Planning and scheduling approaches in real manufacturing environments entail the need to
cope with random attributes and variables to match the characteristics of real scheduling …

In this paper, the research and development project scheduling problem (RDPSP) under
uncertain failure of activities is formulated where an activity's failure results in the project's …

The purpose of this research is to investigate a novel three-stage flow shop scheduling
problem with an ambiguous processing time. The uncertain information is characterized by …

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 …

In real-world manufacturing environments, the execution of a schedule often encounters
uncertain events, which will bring the risks of performance deterioration and production …

Abstract In classic Markov Decision Processes (MDPs), action costs and transition
probabilities are assumed to be known, although an accurate estimation of these …

This paper addresses a two-machine re-entrant flow shop scheduling problem with
stochastic processing times where each job is expected to require a rework phase, flowing …