A stochastic optimization approach to shift scheduling with breaks adjustments

Hur, Youngbum; Bard, Jonathan F.; Frey, M.; Kiermaier, Ferdinand

doi:10.1016/j.cor.2019.03.012

Cited by 14 publications

(6 citation statements)

References 23 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Research efforts around apron equipment and staff (teams) planning have been broadly evolving in two directions: non-collaborative vs. collaborative approaches. The former look to achieve optimized plans for a particular apron service individually, such as transfer buses (Zhao et al 2021), push-back tractors (Bubalo et al 2017), assistants for reducedmobility passengers (Grahn and Jacquillat 2020), or ground handling workers in general (Hur et al 2019). They are most suited to cater for the needs of a single SP.…”

Section: Apron Operations Schedulingmentioning

confidence: 99%

Constraint-based robust planning and scheduling of airport apron operations through simheuristics

et al. 2022

View full text Add to dashboard Cite

Scheduling aircraft turnarounds at airports requires the coordination of several organizations, including the airport operator, airlines, and ground service providers. The latter manage the necessary supplies and teams to handle aircraft in between consecutive flights, in an area called the airport ‘apron’. Divergence and conflicting priorities across organizational borders negatively impact the smooth running of operations, and play a major role in departure delays. We provide a novel simulation-optimization approach that allows multiple service providers to build robust plans for their teams independently, whilst supporting overall coordination through central scheduling of all the involved turnaround activities. Simulation is integrated within the optimization process, following simheuristic techniques, which are augmented with an efficient search driving mechanism. Two tailored constraint-based feedback routines are automatically generated from simulation outputs to constrain the search space to solutions more likely to ensure plan robustness. The two simulation components provide constructive feedback on individual routing problems and global turnaround scheduling, respectively. Compared to the state-of-the-art approach for aircraft turnaround scheduling and routing of service teams, our methodology improves the apron’s on-time punctuality, without the need for the involved organizations to share sensitive information. This supports a wider applicability of our approach in a multiple-stakeholder environment.

show abstract

Section: Apron Operations Schedulingmentioning

confidence: 99%

Constraint-based robust planning and scheduling of airport apron operations through simheuristics

et al. 2022

View full text Add to dashboard Cite

show abstract

“…Most works do target tactical level planning and scheduling problems, especially looking at turnaround teams/employees. Some of the most recent contributions in this direction include Tomasella et al (2019), Gök et al (2020) and Hur et al (2019). Other approaches do exist though.…”

Section: Motivation and Background Literaturementioning

confidence: 99%

Enhanced Operational Management Of Airport Ground Support Equipment For Better Aircraft Turnaround Performance

Saggar

Tomasella²,

Cattaneo³

et al. 2021

2021 Winter Simulation Conference (WSC)

View full text Add to dashboard Cite

Within the context of airport operations, this work focuses on enhancing the planning and real-time allocation of certain resources that are used to turn around an aircraft between two consecutive flights. This sort of operations takes place in the area of an airport that is called its apron. At peak times in particular, and when resource capacity is really tight, apron operations tend to be affected by either unavailability or late arrival of certain assets at the stand. The key element of this paper is the proposal of a new resource booking system, which operates in real-time, and deals with the related uncertainties. The booking mechanism aims to allow the airlines to book in advance certain resources, in particular ground support equipment. Our choice of a real case study will help us to assess the likely benefits, pros and cons of this system.

show abstract

“…Scheduling of meal and rest breaks is not often tackled in the airline crew scheduling literature. Recently, Hur et al [15], [16] investigate a daily shift scheduling problem with flexible breaks under stochastic demand that allows for break adjustments on the day of operation. Kiermaier et al [17] studies the problem of assigning multiple breaks to shifts in the context of large-scale tour scheduling.…”

Section: Literature Reviewmentioning

confidence: 99%

“…In reality, uncertain events, such as short demand perturbations arising from staff absenteeism or customer surge, would cause original employee schedules perform poorly. Motivated by the uncertain factors, there are a growing attentions on accounting for random employee demand in the scheduling models [15], [19]- [23], especially in the context of employee plans in retail stores [10], [24], [25]. In particular, Bürgy et al [25] studies the employee scheduling problem considering uncertain demand arising in retail stores, and their strategy to cope with uncertain demand is assigning overtime work by extending shifts to cope with a lack of employees in real-time.…”

Section: Literature Reviewmentioning

confidence: 99%

Stochastic Check-in Employee Scheduling Problem

et al. 2020

View full text Add to dashboard Cite

This work addresses the problem of assigning airline check-in employees to tasks related to departing flights under uncertain circumstance at an international terminal of a large airport. The uncertainty of flight departing time mainly stems from delays and traffic control. Airlines specifics the minimum and target number of staff for each flight task in each time period. Taking uncertain tasks starting time into account and introducing risk measure (e.g., conditional value-at-risk) into optimization objective function, we present a risk-averse two-stage stochastic model with the mixed-integer recourse that minimizes both staffing costs and risk measurement to respond the time uncertainty. The first-stage decision is to make personal-area allocation plan; and the particular personnel-task scheduling decisions are determined in the second stage as the actual flight departing times are realized. To solve the NP-hard problem, a progressive hedging algorithm is proposed. Numerical experiments are carried out to demonstrate the efficiency and effectiveness of the proposed approach as compared with a sample average approximation method. Finally, we utilize a real-world case to illustrate how the proposed method can be used to obtain a near-optimal solution for practical problem. INDEX TERMS Employee scheduling, stochastic programming, airport ground optimization, risk measure, progressive hedging algorithm.

show abstract

A stochastic optimization approach to shift scheduling with breaks adjustments

Cited by 14 publications

References 23 publications

Constraint-based robust planning and scheduling of airport apron operations through simheuristics

Constraint-based robust planning and scheduling of airport apron operations through simheuristics

Enhanced Operational Management Of Airport Ground Support Equipment For Better Aircraft Turnaround Performance

Stochastic Check-in Employee Scheduling Problem

Contact Info

Product

Resources

About