Titlebook: Optimization and Decision Science: Methodologies and Applications; ODS, Sorrento, Italy Antonio Sforza,Claudio Sterle Conference proceeding

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A Partitioning Based Heuristic for a Variant of the Simple Pattern Minimality Problemrred to as .. In this context, the simple pattern minimality problem (SPMP) arises. It consists in determining the minimum number of patterns “explaining” an initial data set of binary strings. This problem is equivalent to the minimum disjunctive normal form problem and, hence, it has been widely t

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Patient–Centred Objectives as an Alternative to Maximum Utilisation: Comparing Surgical Case Solutiooposed to evaluate the OR planning decisions. Although the OR utilisation is the leading objective, from research experiences, long waiting lists lead to a satisfactory filling of ORs even fixing other objectives. In this paper we analyse the impact on OR utilisation of two patient–centred objective

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A Hierarchical Multi-objective Optimisation Model for Bed Levelling and Patient Priority Maximisatioe been reported to lead and to evaluate the OR planning decisions. Usually, patient priority maximisation and OR utilisation maximisation are the most used objectives in literature. On the contrary, the workload balance criteria, which leads to a smooth ward stay beds occupancy seems less used in li

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Multi-Classifier Approaches for Supporting Clinical Diagnosisgnosis problems are mainly in the scope of the classification problems. Multi-classifier approaches can improve accuracy in classification task. In this work, we propose Multi-classifier approaches based on dynamic classifier selection techniques. These approaches have been tested on datasets known

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Stochastic Dynamic Programming in Hospital Resource Optimizationanagement, are rarely fortunate enough to have all necessary information made available to them at once. In this work we propose a stochastic model for the dynamics of the number of patients in a hospital department with the objective to improve the allocation of resources. The solution is based on

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On the UTA Methods for Solving the Model Selection Problemels, from the best one to the worst one, by means of the comparisons of their global utility values. These values are computed by means of Linear Programming problems. Two UTA methods are illustrated. An example, that examines the performances of some classification models in the web context, is presented.