161 research outputs found
A decision support system for location and allocation problems within a brewery
In this paper we describe a decision support system that was developed for supporting strategical and tactical decision making with respect to location of warehouses and the allocation of customers to warehouses. The system is currently used by the Department of "physical distributions" within Heineken breweries to help management with mid- and longterm logistic decisions. The core of the system is a large mixed integer linear programming model. This paper containes a (long) abstract of the research carried out. A complete description of the results will be submitted for publication elsewhere
An upper bound on the number of non-unique assignments in relaxed (mixed) integer linear programs of the assignment type
An upper bound is given for the number of non-unique assignments when solving the linear programming relaxation of (mixed) integer linear programming problems in which the integer variables are governed by assignment type constraints. Key-words: (mixed) integer linear programming, assignment problems, class-room scheduling
A property of assignment type mixed integer linear programming problems
In this paper we will proof that rather tight upper bounds can be given for the number of non-unique assignments that are achieved after solving the linear programming relaxation of some types of mixed integer linear assignment problems. Since in these cases the number of splitted assignments is small a heuristic can be used to reach a practically good and feasible assignment. Moreover the type of proof can be exploited for related problems to investigate whether a linear programming relaxation will yield mainly integer assignments. Key words: mixed integer linear programming, assignment problems, location allocation problems, distribution problems
Een op lineaire programmering gebaseerd decision support system voor locatie-allocatie planning
Emergency repair of inguinal hernia in the premature infant is associated with high direct medical costs
_Purpose:_ Inguinal hernia repair is frequently performed in premature infants. Evidence on optimal management and timing of repair, as well as related medical costs is still lacking. The objective of this study was to determine the direct medical costs of inguinal hernia, distinguishing between premature infants who had to undergo an emergency procedure and those who underwent elective inguinal hernia repair.
_Methods:_ This cohort study based on medical records concerned premature infants with inguinal hernia who underwent surgical repair within 3 months after birth in a tertiary academic children’s hospital between January 2010 and December 2013. Two groups were distinguished: patients with incarcerated inguinal hernia requiring emergency repair and patients who underwent elective repair. Real medical costs were calculated by multiplying the volumes of healthcare use with corresponding unit prices. Nonparametric bootstrap techniques were used to derive a 95 % confidence interval (CI) for the difference in mean costs.
_Results:_ A total of 132 premature infants were included in the analysis. Emergency surgery was performed in 29 %. Costs of hospitalization comprised 65 % of all costs. The total direct medical costs amounted to €7418 per premature infant in the emergency repair group versus €4693 in the elective repair group. Multivariate analysis showed a difference in costs of €1183 (95 % CI −1196; 3044) in favor of elective repair after correction for potential risk factors.
_Conclusion:_ Emergency repair of inguinal hernia in premature infants is more expensive than elective repair, even after correction for multiple confounders. This deserves to b
Automatic Structure Detection in Constraints of Tabular Data
Abstract. Methods for the protection of statistical tabular data—as controlled tabular adjustment, cell suppression, or controlled rounding— need to solve several linear programming subproblems. For large multi-dimensional linked and hierarchical tables, such subproblems turn out to be computationally challenging. One of the techniques used to reduce the solution time of mathematical programming problems is to exploit the constraints structure using some specialized algorithm. Two of the most usual structures are block-angular matrices with either linking rows (primal block-angular structure) or linking columns (dual block-angular structure). Although constraints associated to tabular data have intrin-sically a lot of structure, current software for tabular data protection neither detail nor exploit it, and simply provide a single matrix, or at most a set of smallest submatrices. We provide in this work an efficient tool for the automatic detection of primal or dual block-angular struc-ture in constraints matrices. We test it on some of the complex CSPLIB instances, showing that when the number of linking rows or columns is small, the computational savings are significant
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
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