Gabriella Dellino

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Optimization of simulated systems is the goal of many methods, but most methods assume known environments. In this paper we present a methodology that does account for uncertain environments. Our methodology uses Taguchi's view of the uncertain world, but replaces his statistical techniques by either Response Surface Methodology or Kriging metamodeling. We(More)
This research aims at supporting hospital management in making prompt Operating Room (OR) planning decisions, when either unpredicted events occur or alternative scenarios or configurations need to be rapidly evaluated. We design and test a planning tool enabling managers to efficiently analyse several alternatives to the current OR planning and scheduling.(More)
This paper addresses the problem of optimal management of consumer flexibility in an electric distribution system. Aggregation of a number of consumers clustered according to appropriate criteria, is one of the most promising approaches for modifying the daily load profile at nodes of an electric distribution network. Modifying the daily load profile is(More)
This paper addresses decomposition methods for Operating Room (OR) planning and scheduling. More specifically, we first focus on determining the Master Surgical Schedule (MSS) on a weekly basis, by assigning the different surgical disciplines to the available sessions. Next, we allocate surgeries to each session, focusing on elective patients only. Patients(More)
Authors only are responsible for the content of this preprint. Abstract In this work, the ability of the Dynamic Objectives Aggregation Methods to solve the portfolio rebalancing problem is investigated conducting a computational study on a set of instances based on real data. The portfolio model considers a set of realistic constraints and entails the(More)
Acknowledgements Now that I become closer and closer to the end of this adventure, I would like to deeply thank some people who helped me — in different ways and at different stages of my PhD — to achieve this goal. First of all, I want to thank my advisors: Carlo Meloni, for having introduced me to the fascinating world of research, for his being always so(More)