Evaluation of the quantiles and superquantiles of the makespan in interval valued activity networks

Meloni, Carlo; Pranzo, Marco

doi:10.1016/j.cor.2022.106098

Cited by 2 publications

(1 citation statement)

References 69 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Kasperski and Zieliński (2019) discussed a wide class of single-machine scheduling problems with uncertain job processing times and due dates and applied risk measure criteria (VaR and CVaR) to obtain an optimal solution. Meloni and Pranzo (2020) evaluated the conditional value-at-risk of the makespan for a resource-constrained project scheduling problem where, for each activity, an interval for processing times is defined in the integer domain and the evaluation of quantile-and superquantiles-based risk measures for the interval-valued processing times in scheduling problems is addressed in Meloni and Pranzo (2023). Several researchers also proposed heuristic approaches for stochastic scheduling problems considering risk measures (Rezaei et al 2020;Villarinho et al 2021).…”

Section: Literature Reviewmentioning

confidence: 99%

A branch-and-bound approach to minimise the value-at-risk of the makespan in a stochastic two-machine flow shop

Liu

Urgo

2023

International Journal of Production Research

View full text Add to dashboard Cite

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 problems where uncertain events are frequent. Moreover, the capability of devising robust schedules, which are less sensitive to the disruptive effects of unexpected events, is a major request in real applications. In this paper, a branch-and-bound approach is proposed to solve the two-machine permutation flow shop scheduling problem with stochastic processing times. The objective is the minimisation of the value-at-risk of the makespan, to support decisionmakers in the trade-off between the expected performance and the mitigation of the impact of extreme scenarios. A Markovian Activity Network (MAN) model is adopted to estimate the distribution of the makespan and assess the value-at-risk for both partial and complete schedules. Phasetype distributions are used to enable general distributions for processing times while maintaining the capability to exploit a Markovian approach. The effectiveness and performance of the proposed approach are demonstrated through a set of computational experiments.

show abstract