Optimised buffer allocation to construct stable personnel shift rosters

Ingels, Jonas; Maenhout, Broos

doi:10.1016/j.omega.2017.12.006

Cited by 19 publications

(12 citation statements)

References 35 publications

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“…The working order of flight crews in airlines is done through the task listing and tracking method called roster. Airlines need to establish stable core personnel shift teams based on predictions about future staff demand and employee availability (Ingels, and Meanhout, 2017). In order to make instant changes in the personnel shift list, capacity buffers are created, in which some personnel are kept in reserve or ready.…”

Section: Methodsmentioning

confidence: 99%

Investigation Of The Relationship Between The Personality, Organizational Identification and Turnover In Competitive Flight Model

et al. 2021

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The aim of this study is to analyze the employees of the low cost carriers (LCC) and Full Service Carriers (FSC) personal traits, organizational indentification and Turnover. The research data were collected by the Personality Traits Scale and Turnover Scale. The sample consisted of 175 working in the LCC business model and 175 working in the FSC business model. The models obtained by the path analysis for the research variables were statistically tested and fit indices were investigated for each model. It was determined that the Organizational Identification (OI) has a full mediating effect on the relationship between the Emotinonal Stability (ES) and the Turnover (TO) in the LCC business model. In the same way, employees working in the full service airline business model; In the effect of ES variable on TO variable, OI variable was determined to have full mediating effect. When structural equation model is applied to the data obtained from all partipicipants, it is determined that the OI variable has a partial mediating effect on the effect of the Conscientiousness (C) on the TO. It can be thought that the research findings will contribute to airline human resources professionals and researchers in strategic planning.

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Section: Methodsmentioning

confidence: 99%

Investigation Of The Relationship Between The Personality, Organizational Identification and Turnover In Competitive Flight Model

et al. 2021

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“…Better than a general surcharge are concrete buffers for service agents, which should be defined based on a case specific procedure. Ingels and Maenhout [10] examine how to define optimal buffers by including them in their optimization model to increase roster robustness. Doing this, they create a roster with greater stability against unforeseen disruptions.…”

Section: Staff Rostering In Call Centersmentioning

confidence: 99%

“…In this paper, we are looking at the uncertainty of capacity, as service agents represent human resources and their presence cannot be taken for granted. There are several strategies to deal with such uncertainty, including: Substitutions of probably absent service agents, reserve shifts for reactive substitution or a general increase in staff demand in order to cover possible absences [3,[6][7][8][9][10]. Another more sophisticated option is using predictive analytics to estimate staff absences [3,9,11] and to adjust the roster accordingly.…”

Section: Introductionmentioning

confidence: 99%

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2020

Int J Ind Operations Res

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Staff rostering is a crucial task in inbound call centers, as personnel costs usually account for the largest share of operating costs. Uncertainty of capacity, such as the presence of agents is often disregarded during rostering. This paper addresses the problem of uncertainty by using predictive analytics to predict agent absences and thus increase roster robustness. Operational data from four years of a call center serves as a basis for our use case. Predictors include characteristics of the service agents such as attendance history and regular working hours as well as other factors such as the weekday. Of the prediction algorithms tested, decision trees outperform other predictive modeling approaches. Evaluation based on an expected value framework shows that the predictive analytics approach performs best compared to the planned, unchanged roster and a general staff surcharge of 10%.

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“…Most of them are random and cannot be anticipated in advance. Such events are henceforth referred to as disruptions [9].…”

Section: Introductionmentioning

confidence: 99%

Interactive Planning of Competency-Driven University Teaching Staff Allocation

et al. 2020

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This paper focuses on a teacher allocation problem that is specifically concerned with assigning available academic lecturers to remaining courses from a given student curriculum. The teachers are linked to tasks according to competencies, competence requirements enforced by the curriculum as well as the number and type of disruptions that hamper the fulfilment of courses. The problem under consideration boils down to searching links between competencies possessed by teachers and competencies required by the curricula that will, firstly, balance student needs and teacher workload and, secondly, ensure an assumed robustness level of the teaching schedule. The implemented interactive method performs iterative solving of analysis and synthesis problems concerned with alternative evaluation/robustness of the competency framework. Its performance is evaluated against a set of real historical data and arbitrarily selected sets of disruptions. The computational results indicate that our method yields better solutions compared to the manual allocation by the university.

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Optimised buffer allocation to construct stable personnel shift rosters

Cited by 19 publications

References 35 publications

Investigation Of The Relationship Between The Personality, Organizational Identification and Turnover In Competitive Flight Model

Investigation Of The Relationship Between The Personality, Organizational Identification and Turnover In Competitive Flight Model

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Interactive Planning of Competency-Driven University Teaching Staff Allocation

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