Operating theatre modelling: integrating social measures

Hospital resource modelling literature is primarily focussed on productivity and efficiency measures. In this paper, our focus is on the alignment of the most valuable revenue factor, the operating room (OR) with the most valuable cost factor, the staff. When aligning these economic and social decisions, respectively, into one sustainable model, simulation results justify the integration of these factors. This research shows that integrating staff decisions and OR decisions results in better solutions for both entities. A discrete event simulation approach is used as a performance test to evaluate an integrated and an iterative model. Experimental analysis show how our integrated approach can benefit the alignment of the planning of the human resources as well as the planning of the capacity of the OR based on both economic related metrics (lead time, overtime, number of patients rejected) and social related metrics (personnel preferences, aversions, roster quality)

Statistical disclosure control in tabular data

Data disseminated by National Statistical Agencies (NSAs) can be classified as either microdata or tabular data. Tabular data is obtained from microdata by crossing one or more categorical variables. Although cell tables provide aggregated information, they also need to be protected. This chapter is a short introduction to tabular data protection. It contains three main sections. The first one shows the different types of tables that can be obtained, and how they are modeled. The second describes the practical rules for detection of sensitive cells that are used by NSAs. Finally, an overview of protection methods is provided, with a particular focus on two of them: “cell suppression problem” and “controlled tabular adjustment”.Postprint (published version

A fix-and-relax heuristic for controlled tabular adjustment

Controlled tabular adjustment (CTA) is an emerging protect ion technique for tabular data pro- tection. CTA formulates a mixed integer linear programming problem, which is tough for tables of moderate size. Finding a feasible initial solution may ev en be a challenging task for large instances. On the other hand, end users of tabular data prote ction techniques give priority to fast executions and are thus satisfied in practice with suboptima l solutions. In this work the fix-and- relax strategy is applied to large CTA instances. Fix-and-r elax is based on partitioning the set of binary variables into clusters to selectively explore a sma ller branch-and-cut tree. We report ex- tensive computational results on a set of real and random CTA instances. Fix-and-relax is shown to be competitive compared to plain CPLEX branch-and-cut in terms of quickly finding either a feasible solution or a good upper bound in di ffi cult instances.Preprin

Design and Implementation of Takagi-Sugeno Fuzzy Tracking Control for a DC-DC Buck Converter

This paper presents the design and implementation of a Takagi-Sugeno (T-S) fuzzy controller for a DC-DC buck converter using Arduino board. The proposed fuzzy controller is able to pilot the states of the buck converter to track a reference model. The T-S fuzzy model is employed, firstly, to represent exactly the dynamics of the nonlinear buck converter system, and then the considered controller is designed on the basis of a concept called Virtual Desired Variables (VDVs). In this case, a two-stage design procedure is developed: i) determine the reference model according to the desired output voltage, ii) determine the fuzzy controller gains by solving a set of Linear Matrix Inequalities (LMIs). A digital implementation of the proposed T-S fuzzy controller is carried out using the ATmega328P-based Microcontroller of the Arduino Uno board. Simulations and experimental results demonstrate the validity and effectiveness of the proposed control scheme

Extending controlled tabular adjustment for non-additive tabular data with negative protection levels

Minimum distance controlled tabular adjustment (CTA) is a recent perturbative methodology for the protection of tabular data. An implementation of CTA was recently used by Eurostat for the protection of European Union level structural business and animal production statistics. The realworld instances to be solved forced the classical CTA model to be extended with two features: first, to deal with non-additive tables; second, and most important, to consider negative protection levels. The latter extension means a significant modification of the classical CTA mixed integer linear model. We present and compare new models for these extensions. Computational results are reported using a set of real-world instances, and two state-of-the-art commercial solvers (CPLEX and Xpress)