Philippe De Bruecker

Personnel scheduling: A literature review

This paper presents a review of the literature on personnel scheduling problems. Firstly, we discuss the classification methods in former review papers. Secondly, we evaluate the literature in the many fields that are related to either the problem setting or the technical features. Each perspective is presented as a table in which the classification is displayed. This method facilitates the identification of manuscripts related to the reader’s specific interests. Throughout the literature review, we identify trends in research on personnel staffing and scheduling, and we indicate which areas should be subject to future research.

Workforce planning incorporating skills: state of the art

This paper presents a review and classification of the literature regarding workforce planning problems incorporating skills. In many cases, technical research regarding workforce planning focuses very hard on the mathematical model and neglects the real life implications of the simplifications that were needed for the model to perform well. On the other hand, many managerial studies give an extensive description of the human implications of certain management decisions in particular cases, but fail to provide useful mathematical models to solve workforce planning problems. This review will guide the operations researcher in his search to find useful papers and information regarding workforce planning problems incorporating skills. We not only discuss the differences and similarities between different papers, but we also give an overview of the managerial insights. The objective is to present a combination of technical and managerial knowledge to encourage the production of more realistic and useful solution techniques.

Integrated staffing and scheduling for an aircraft line maintenance problem

This paper studies the problem of constructing the workforce schedules of an aircraft maintenance company. The problem involves both a staffing and a scheduling decision. We propose an enumerative algorithm with bounding in which each node of the enumeration tree represents a mixed integer linear problem (MILP). We reformulate the MILP such that it becomes tractable for commercial MILP solvers. Extensive computational tests on 40 instances that are derived from a real-life setting indicate that the algorithm is capable of finding close-to-optimal solutions.

A three-stage approach for aircraft line maintenance personnel rostering using MIP, discrete event simulation and DEA

Personnel scheduling problems need to cope with personnel preferences, coverage constraints, legal restrictions, and many other constraints. We present a three-stage methodology that can be used to select personnel rosters. In the first stage we generate multiple personnel rosters with a mathematical programming model. In the second stage, the performance of the rosters regarding a number of service criteria is evaluated through discrete event simulation. In the third stage, a ranking is made using data envelopment analysis. The methodology is tested on a personnel scheduling problem for aircraft line maintenance.

A model enhancement heuristic for building robust aircraft maintenance personnel rosters with stochastic constraints

This paper presents a heuristic approach to optimize staffing and scheduling at an aircraft maintenance company. The goal is to build robust aircraft maintenance personnel rosters that can achieve a certain service level while minimizing the total labor costs. Robust personnel rosters are rosters that can handle delays associated with stochastic flight arrival times. To deal with this stochasticity, a model enhancement algorithm is proposed that iteratively adjusts a mixed integer linear programming (MILP) model to a stochastic environment based on simulation results. We illustrate the performance of the algorithm with a computational experiment based on real life data of a large aircraft maintenance company located at Brussels Airport in Belgium. The obtained results are compared to deterministic optimization and straightforward optimization. Experiments demonstrate that our model can ensure a certain desired service level with an acceptable increase in labor costs when stochasticity is introduced in the aircraft arrival times.

A model enhancement approach for optimizing the integrated shift scheduling and vehicle routing problem in waste collection

Abstract This paper presents a model enhancement approach for the integrated problem of developing shift schedules and waste collection routes. Given a variable amount of waste to be collected the objective is to find fixed, minimal cost shift schedules and collection routes under a service level constraint. While regular shifts during traffic peak hours are cheaper in terms of labour costs, the collection speed is on average lower than during expensive, non-regular shifts. Our findings can be summarized as follows. (1) Solutions can be found within reasonable computation time for real-life instances. (2) The model enhancement approach accurately estimates the required collection times and therefore consistently finds a feasible solution. (3) The solutions not only result in considerable savings, but are also proven to be (near)optimal by comparison with a practical lower bound based on flexible routes.

A Two-Stage Mixed Integer Programming Approach for Optimizing the Skill Mix and Training Schedules for Aircraft Maintenance

This paper presents a two-stage mixed integer programming approach for optimizing the skill mix and training schedule at the aircraft maintenance company Sabena Technics. Of course, when all workers are trained for all skills, cheaper workforce schedules are possible. However, the training that is required to acquire all those skills can become very expensive. In the first stage of our two-staged approach, we therefore make a trade-off between the training costs and the resulting cheaper workforce schedule. As we assume that workers are unavailable to work during their training, the obtained result is only applicable in practice if the required training can be performed without endangering the current maintenance operations. In the second stage, we therefore want to find an optimal and feasible training schedule in order to obtain the desired skill mix with minimal costs. We illustrate our models with a computational experiment based on real-life data of Sabena Technics.

Optimizing the Workforce Schedule and Collection Routes for Glass Containers

This paper presents and compares two different solution approaches to optimize the glass collection process at a single intermunicipal authority in Belgium. First, a model enhancement approach is proposed to solve a shift scheduling optimization problem integrating the construction of glass collection routes. Second, a simulation based rolling horizon procedure is designed to determine the possible benefits of providing the glass containers with fill level sensors. The performance of both solution approaches is evaluated and compared using real-life data.

A Tabu Search Heuristic for Building Aircraft Maintenance Personnel Rosters

This paper presents a fast heuristic approach to optimize staffing and scheduling of the workforce at an aircraft maintenance company. Two linked Tabu Search algorithms are proposed to minimize the labour costs and to maximize employee satisfaction. To enhance the performance of the algorithm, strategic oscillation and pattern creation are used. We illustrate the performance of the algorithms with a computational experiment based on real life data from Sabena Technics, a large aircraft maintenance company located at Brussels Airport in Belgium. We analyze the results in different scenarios and compare them to a mixed integer linear programming model. The experiments demonstrate that Tabu Search can deliver acceptable solutions faster than the integer programming technique for small instances and outperforms the integer programming model for larger and more realistic problem sizes.