Jully Jeunet

We consider the problem of scheduling non preemptively a set of jobs on parallel identical machines with prior setup operations on a single shared server, where the objective is to minimise the makespan. We develop an arc-flow formulation to the problem with two multigraphs, one for the machines and one for the server, with a same set of nodes representing points in time, and arcs associated with job execution, and with machines or server idleness. The resulting Flow-Flow formulation (FFF) and its tuned version (FFT) are compared with the best existing model in the literature, TIV I, on benchmark instances with up to 200 jobs and 7 machines. Computational results showed that our Flow-Flow models outperformed TIV I for instances with 100 jobs and produced optimal solutions to the vast majority of problems with 150 and 200 jobs for which TIV I failed to even find integer solutions within the standard limited runtime of 3600 s. When non optimal, solutions provided by our models exhibited very low gaps to best bound.

We address the discrete time break scheduling problem with no preemption when workers' fatigue impacts their productivity. We propose a Mixed Integer Linear Programming model to solve the one break problem to optimality, using a lexicographic approach where the production amount is maximised first, and then the break length over a discrete time horizon. We develop a Variable Neighbourhood Search algorithm to solve the multiple break problem. In addition to proposing efficient solution methods to the problem, our incentive is to assess the impact on the production amount and on workers' welfare of rest break regulations laid down in legislation or collective agreements. We conducted an extensive simulation study to represent a wide range of workers' profiles defined in terms of fatigability and recovery speed. Simulation results show that regulations slightly affect the production amount whereas they allow for large improvements of workers' welfare as long as breaks are optimised as a second objective. The production amount is also shown to be quite sensitive to the break timing. Finally, multiple breaks can improve the production amount and workers' welfare in many situations, which questions the widespread belief that endowing workers with a single short break would optimise the production amount.

In the literature, tactical plans of elective patients aim at increasing hospital efficiency through a better resource utilisation, although hospitals claim that patient satisfaction, usually measured by the waiting time, is also important. In this regard, the purpose of this paper is to show how patient satisfaction can be associated with any tactical plan, by developing a method to compute exact waiting time distributions. We also present a procedure to calculate the exact levels of resource utilisation. Therefore, with our procedures, hospital managers can determine the operational performance of their tactical plan. We then explore two strategies to improve tactical plans in terms of waiting time: slack planning and smooth allocation. A case study based on data from a Dutch cardiothoracic surgery centre shows that slack planning leads to a trade-off between waiting time and hospital efficiency. When slack planning is combined to smooth allocation, additional improvements of the waiting time can be reached.