Nadine Meskens

A planning and scheduling problem for an operating theatre using an open scheduling strategy

The objective of this paper is to design a weekly surgery schedule in an operating theatre where time blocks are reserved for surgeons rather than specialities. Both operating rooms and places in the recovery room are assumed to be multifunctional, and the objectives are to maximise the utilisation of the operating rooms, to minimise the overtime cost in the operating theatre, and to minimise the unexpected idle time between surgical cases. This weekly operating theatre planning and scheduling problem is solved in two phases. First, the planning problem is solved to give the date of surgery for each patient, allowing for the availability of operating rooms and surgeons. Then a daily scheduling problem is devised to determine the sequence of operations in each operating room in each day, taking into account the availability of recovery beds. The planning problem is described as a set-partitioning integer-programming model and is solved by a column-generation-based heuristic (CGBH) procedure. The daily scheduling problem, based on the results obtained in the planning phase, is treated as a two-stage hybrid flow-shop problem and solved by a hybrid genetic algorithm (HGA). Our results are compared with several actual surgery schedules in a Belgian university hospital, where time blocks have been assigned to either specific surgeons or specialities several months in advance. According to the comparison results, surgery schedules obtained by the proposed method have less idle time between surgical cases, much higher utilisation of operating rooms and produce less overtime.

An operating theatre planning and scheduling problem in the case of a "block scheduling" strategy

Operating theatre is always the most important and expensive sector of the hospital, and its surgical process management problem is always regarded as the kernel. In this paper, we focus on one of the surgical process management problems: block scheduling problem. An efficient weekly operating program is built for an operating theatre through two phases: at first the operating theatre weekly planning problem is solved with a heuristic procedure based on column generation procedure; then the operating theatre daily scheduling problem, based on the results from the first phase, is solved with a hybrid genetic algorithm. In the end, the proposed problem is tested and validated with randomly generated data, and then the numerical results are provided

A comparison of rough sets and recursive partitioning induction approaches : an application to commercial loans

Credit scoring is the term used to describe methods utilised for classifying applicants for credit into classes of risk. This paper evaluates two induction approaches, rough sets and decision trees, as techniques for classifying credit (business) applicants. Inductive learning methods, like rough sets and decision trees, have better knowledge representational structure than neural networks or statistical procedures because they can be used to derive production rules. If decision tree have already been used for credit granting, the rough sets approach is rarely utilised in this domain. In this paper, we use production rules obtained on a sample of 1102 business loans in order to compare the classification abilities of the two techniques. It results that decision tree obtains better results with 87.5% of good classifications with a pruned tree against 76.7% for rough sets. However, decision tree make more type II errors than rough sets but less type I errors.

Business Failure Prediction: A Review and Analysis of the Literature

Business failure prediction is a topic of great importance for a lot of people (shareholders, banks, investors, suppliers,…). That’s why a lot of models were developed in order to predict it. Statistical procedures (multiple discriminant analysis, logit or probit) were among the most used methods in this kind of problem. However, parametric statistical methods require the data to have a specific distribution. In addition to the restriction on the distribution involved, multi-collinearity, autocorrelation and heteroscedasticity could lead to problems with the estimated model with some statistical methods. Because of these drawbacks, others methods have been investigated: multicriteria methods (i.e. UTA, Electre tri,…) or machine learning methods (i.e. neural network, genetic algorithm, decision tree, instance based learning,…). Our main target is to provide a review of the literature but also to have a larger view than usually by evoking causes, symptoms and remedies of bankruptcy. We also proposed new perspectives and topics of research.

Multicriteria optimisation and simulation: an industrial application

Abstract This paper deals with multicriteria discrete-continuous problems of scheduling nonpreemptable jobs. The need for reusability and modularity leads us to build a “generic” optimisation and simulation framework, while the need to quickly generate good compromises between conflicting objectives requires the implementation of multicriteria scheduling models. This paper describes the practical possibilities of three hybrid models within this framework. The validation of the framework is presented in terms of its application to a real, highly constrained, discrete-continuous problem. The optimisation model is based on the hybridisation of a classical hill-climber meta-heuristic with the Promethee II multicriteria method.

Using constraint programming to schedule an operating theatre

The daily operating rooms scheduling is a highly constrained problem. It is also hard to find an optimal solution or at least high quality solutions. To solve this scheduling problem, we use the “expressive power” of the constraint programming paradigm to include as many as possible real-life constraints in our model, such as the availability and the preferences of the staff. We develop a “generic” adaptive model which embeds most of the characteristics of the problem encountered in the literature as well as real-life constraints coming from practical problems in hospitals.

Surgical scheduling with antagonistic human resource objectives

Daily operating theatre scheduling is a complex problem with strong constraints and various objectives to optimise. In this article, we aim not only to optimise the classical objectives of scheduling performance, such as the makespan and the cost of overtime, but also, particularly, to upgrade human resource management performance by means of two additional objectives: a short-term objective on the quality of teamwork and a long-term objective on the level of nurses’ skills. The quality of teamwork depends on affinities between team members, which also have a significant impact on the quality and the safety of surgery. It maintains the unity of surgical teams. Such unity is however unfavourable to nurses’ skill diversification. In order to counterbalance this tendency, the long-term objective proposed is for nurses to acquire the widest possible spectrum of skills, in order to be able to assist surgeons in unplanned and emergency surgery. Taking into account these two antagonistic human resources objectives contributes to patient safety through better team building. It is the main originality of this work. In the long term, this method reduces the impact of this antagonism. In addition, we use the multi-objective ε-constraint method to obtain Pareto optimal solutions.

Comparaison des performances des politiques de programmation opératoire

La planification des interventions chirurgicales est un exercice complexe qui constitue le noyau central de la gestion d’un bloc opératoire, un lieu hautement stratégique dans une structure hospitalière. Elle consiste à affecter des interventions à des salles d’opérations et des créneaux horaires en respectant les contraintes humaines et matérielles. L’objectif est deminimiser les coûts, les délais et d’augmenter la qualité des soins ainsi que la satisfaction des patients. Dans cet article, uneméthode de planification est appliquée dans le cadre du bloc opératoire d’un hôpital universitaire Belge. Le but est demontrer son apport dans le cadre de différentes politiques de programmation opératoire.

Strategic and Tactical Hospital Bed Management in Belgium and in France

Nowadays, lots of healthcare establishments decide to integrate a hospital bed management department, while taking into account the financial impact on the budget, the disruptions and factors influencing the bed planning as e.g. the type of care units management and the existing networks between hospitals and satellite structures. Lots of constraints will also have an impact while optimizing the available resources: accepting the emergency case and therefore delaying the planned patient, adding additional beds within a care unit and studying at the same time the collateral costs, opening or closing beds related to a specialty, etc.

Supply chain issues and opportunities

Advances in the development of new information and communication technologies coupled with the fierce competition have a deep impact on the development and positioning of current companies on international market places. To respond to the market changing conditions, firms have to rethink the layout of their supply chain, the management of their logistic systems and the development of partnership relations with their suppliers and customers. A firm can thus no longer be considered as an isolated entity but as a component of a wider supply network. Both academics and industrialists have been interested by different issues of this thematic. The International conference on Industrial Engineering and Production Management IEPM03, May 2003, Porto, focused on specific issues of the global supply chain with a special emphasis on logistics management and optimization. Participants had the possibility to identify emerging industrial issues and research opportunities in the area of Supply Chain Management. The papers presented in this special edition of the journal were selected among the best contributions discussed at the IEPM conference. They present substantial advances in the research on the supply chain in a wide variety of contexts and applications.