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Brecht Cardoen

Researcher at Katholieke Universiteit Leuven

Publications -  43
Citations -  2404

Brecht Cardoen is an academic researcher from Katholieke Universiteit Leuven. The author has contributed to research in topics: Integer programming & Scheduling (computing). The author has an hindex of 17, co-authored 40 publications receiving 2119 citations. Previous affiliations of Brecht Cardoen include Catholic University of Leuven.

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Operating room planning and scheduling: A literature review

TL;DR: A diversified and detailed overview of recent operational research on operating room planning and scheduling is obtained that facilitates the identification of manuscripts related to the reader's specific interests.
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Optimizing a multiple objective surgical case sequencing problem

TL;DR: The optimization problem is NP-hard and some mixed integer linear programming solution approaches are developed, which are either exact or heuristic in nature, to facilitate the decision process of the operating room scheduler.
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A decision support system for cyclic master surgery scheduling with multiple objectives

TL;DR: A decision support system for cyclic master surgery scheduling that relies on mixed integer programming techniques involving the solution of multi-objective linear and quadratic optimization problems, and on a simulated annealing metaheuristic is presented.
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Sequencing surgical cases in a day-care environment: An exact branch-and-price approach

TL;DR: This paper investigates how to sequence surgical cases in a day-care facility and applies column generation to solve this combinatorial optimization problem and proposes a dynamic programming algorithm to solve the pricing problem.
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Scheduling operating rooms: achievements, challenges and pitfalls

TL;DR: The recent OR planning and scheduling literature is classified into tables regarding patient type, used performance measures, decisions made, OR up- and downstream facilities, uncertainty, research methodology and testing phase, to help researchers and practitioners to select new relevant articles.