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Chronic patients suffering from non-communicable diseases are often enrolled into a diagnostic and therapeutic care program featuring a personalized care plan. Healthcare is mostly provided at the patient's home, but those examinations and treatments that must be delivered at the hospital have to be explicitly booked. Booking is not trivial due to, on the one hand, the several time constraints that become particularly tight in the case of comorbidity, on the other hand, the limited availability of both staff and equipment at the hospital care units. This suggests that the scheduling of the clinical pathways for enrolled outpatients should be managed in a centralized manner, taking advantage of the fact that demand for services is known well in advance. The aim is to serve as many requests as possible (unattended requests are supplied by contracted private health facilities) in a timely manner, taking patients priority into account. Booking involves setting a date and a time for each selected health service, which is rather complex. In this work, we provide a declarative approach by encoding the problem in Answer Set Programming (ASP). In order to improve the scalability of the ASP approach, we present and compare two heuristic approaches, respectively based on service demand and time decomposition. All approaches are tested on instances of increasing size to assess scalability with respect to time horizon and number of requests. [ABSTRACT FROM AUTHOR]

Echo-doppler examination of the jugular vessel is a powerful tool for the early diagnosis of cardiovascular disorders that can be further related to central nervous system diseases. Unfortunately, the ultrasound technique is strongly operator-dependent, so the quality of the scan, the accuracy of the measurement, and therefore the rapidity and robustness of the diagnosis reflect the degree of training. The paper presents the development of a mechatronic simulation system for improving the skill of novice physicians in echo-doppler procedures. The patient is simulated by a silicone manikin whose materials are designed to have a realistic ultrasound response. Two tubes allow blood-mimicking fluid to flow inside the manikin, simulating the hemodynamics of the internal jugular vein. The mechatronic system is designed for controlling the flow waveform, to reproduce several clinical cases of interest for diagnosis. The experiments investigate the accuracy of the echo-doppler measurements performed on the proposed system by novice operators using a real ultrasound scanner. [ABSTRACT FROM AUTHOR]

The demand-adaptive systems studied in this paper attempt to offer demand-responsive services within the framework of traditional scheduled bus transportation: Users call to request service between two given points and, […]

The recent SARS CoV-02 pandemic has put enormous pressure on intensive care staff, making it imperative to relieve them of repetitive tasks with little added value such as drug replenishment. We propose a decision support system based on a hybrid policy to manage the inventory of critical drugs with low and intermittent demand at an Intensive Care Unit (ICU). Demand forecasting is at the heart of any inventory policy. We claim that in the ICU setting drug demand patterns must be therapy based. Heterogeneous data have been collected during an on site study, and information have been extracted to provide a faithful abstract representation of the ward as a system, as well as the potential evolutions of ICU patients clinical conditions. Together with medical guidelines, this provides the foundation of a therapy based demand forecasting tool. This study integrates schedule optimization and demand forecasting, and exploits simulation for evaluation purpose in the long run. At the beginning of every period, drug orders are optimally scheduled with respect to forecast demand. Then, scheduled orders are deployed day by day and confronted with the real demand in a simulated environment. Potential stock outs trigger rush orders to restore safety stocks. The comparison between the proposed policy and a standard policy mimicking current practice in an ICU ward shows that information on therapy patterns can be successfully incorporated into drug replenishment processes to reduce the number of rush orders, a primary goal in designing an efficient system. [ABSTRACT FROM AUTHOR]

When demand for transportation is low or sparse, traditional transit cannot provide efficient and good-quality service, because of its fixed structure. For this reason, mass transit is evolving toward some degree of flexibility. Although the extension of Dial-a-Ride systems to general public meets such need of adaptability, it presents several drawbacks mostly related to the their extreme flexibility. Consequently, new transportation alternatives, such as demand-adaptive systems (DASs), combining characteristics from both the traditional transit and Dial-a-Ride, have been introduced. For their twofold nature, DASs require careful planning. We focus on tactical aspects of the planning process by formalizing the single-line DAS design problem with stationary demand and proposing two alternative hierarchical decomposition approaches for its solution. The main motivation behind this work is to provide a general methodology suitable to be used as a tool to build the tactical DAS plan in real-life conditions. We provide an experimental study where the two proposed decomposition methods are compared and the general behavior of the systems is analyzed when altering some design parameters. Furthermore, we test the versatility of our methods on a variety of situation that may be encountered in real-life conditions. [ABSTRACT FROM AUTHOR]

One promising trend in digital system integration consists of boosting on-chip communication performance by means of silicon photonics, thus materializing the so-called Optical Networkson-Chip. Among them, wavelength routing can be used to route a signal to destination by univocally associating a routing path to the wavelength of the optical carrier. Such wavelengths should be chosen so to minimize interferences among optical channels and to avoid routing faults. As a result, physical parameter selection of such networks requires the solution of complex constrained optimization problems. In previous work, published in the proceedings of the International Conference on Computer-Aided Design, we proposed and solved the problem of computing the maximum parallelism obtainable in the communication between any two endpoints while avoiding misrouting of optical signals. The underlying technology, only quickly mentioned in that paper, is Answer Set Programming. In this work, we detail the Answer Set Programming approach we used to solve such problem. Another important design issue is to select the wavelengths of optical carriers such that they are spread across the available spectrum, in order to reduce the likelihood that, due to imperfections in the manufacturing process, unintended routing faults arise. We show how to address such problem in Constraint Logic Programming on Finite Domains. [ABSTRACT FROM AUTHOR]

Water contamination events in a urban hydraulic network can be handled by operating two types of network devices: valves, to divert flow, and hydrants, to dispel flow. No remote control can activate these devices, which must be operated on site, therefore teams of technicians have to move from device to device on the city streets. The response to the contamination corresponds to a feasible schedule of the devices' activation times, which can be modelled as a multiple Travelling Salesman Problem; the quality of the schedule is the volume of contaminated water consumed by the users until water quality returns to safety levels. This quantity is highly sensitive to the schedule and is computed by way of a computational demanding hydraulic simulation, which takes about 5 seconds for the Ferrara's hydraulic network serving around 130'000 citizens. Previous studies proved that minimizing the makespan, as it would be intuitive in case of emergency, yields worse solutions than random approaches. Genetic Algorithms were proposed to optimize the schedules, however they converge to local optima, depending on the initial population. We propose to apply Path Relinking to explore the space between pairs of local optima; the experiments showed that this technique improves the local best. This work is a follow up of what presented at AIxIA2015, enpowered with a light introduction to Path Relinking and its applications. Moreover, the experimental campaign has been extended on a larger set of scenarios, i.e. 42 contamination scenarios, to gain more insight into the performance of the proposed methodology. [ABSTRACT FROM AUTHOR]

Positioning of valves is a real-life issue in Water Distribution System (WDS) design and, currently, it is usually addressed by hydraulic engineers either by hand or by means of genetic algorithms, that give no assurance of optimality. Since a given valves placement identifies a sectorization of the WDS in several isolable portions, the valves positioning problem can be seen as a variant of the well known graph partitioning problem, which is a hard combinatorial problem. Cattafiet al. (2011, TPLP, 11, 731-747) showed recently that Computational Logic can provide technologies and techniques that can be exploited to model and achieve the optimal partition of the water network (i.e. the optimal positioning of valves). In particular, the authors tackled the optimization of the valves positioning through a two player game model, giving a Constraint Logic Programming formalization to solve it effectively. The aim of this article, instead, is to investigate the potential of Answer Set Programming in this practical application; evaluation is in terms both of language expressivity and solving efficiency. Results are discussed for different ASP models and a comparison with the CLP(FD) technique shown by Cattafiet a l.(2011, TPLP, 11, 731-747) will be given. [ABSTRACT FROM AUTHOR]

This paper heuristically tackles a challenging scheduling problem arising in the field of hydraulic distribution systems in case of a contamination event, that is, optimizing the scheduling of a set of tasks so that the consumed volume of contaminated water is minimized. Each task consists of manually activating a given device, located on the hydraulic network of the water distribution system. In practice, once contamination has been detected, a given number of response teams move along the network to operate each device on site. The consumed volume of contaminated water depends on the time at which each device is operated, according to complex hydraulic laws, so that the value associated to each schedule must be evaluated by a hydraulic simulation.We explore the potentials of Genetic Algorithms as a viable tool for tackling this optimization-simulation problem. We compare different encodings and propose ad hoc crossover operators that exploit the combinatorial structure of the feasible region, featuring hybridization with Mixed Integer Linear Programming.Extensive computational results are provided for a real life hydraulic network of average size, showing the effectiveness of the approach. Indeed, we greatly improve upon common sense inspired solutions which are commonly adopted in practice. [ABSTRACT FROM AUTHOR]

Although sometimes it is necessary, no one likes to stay in a hospital, and patients who need to stay in bed but do not require constant medical surveillance prefer their own bed at home. At the same time, a patient in a hospital has a high cost for the community, that is not acceptable if the patient needs service only a few minutes a day. For these reasons, the current trend in Europe and North-America is to send nurses to visit patients at their home: this choice reduces costs for the community and gives better quality of life to patients. The challenge is to deliver the service in a cost effective manner without a detriment of the service quality. These social and health management issues have interesting implications from the mathematical viewpoint, introducing a challenging combinatorial optimization problem. The problem consists in assigning patients' services to traveling nurses and defining the nurse itineraries so that the following optimization aspects are considered: the nurse workloads (including service as well as travel time) are balanced, patients are preferentially served by a single nurse or just a few ones, and the overall travel time is minimized. These objectives are somehow conflicting and a reasonable trade off must be found. The complexity of the problem calls for suitable optimization-based algorithmic support to decisions, in particular in the perspective of an increasing diffusion of the service.This problem is known in the literature as the Home Health Care (HHC) problem. In this paper, we address the HHC problem in the municipality of Ferrara, a mid-sized city in the North of Italy. The problem is currently solved by hand, starting from a partitioning of patients based on predefined zones. We describe a Constraint Programming model that solves the HHC problem, and show significant improvements with respect to the current manual solution. [ABSTRACT FROM AUTHOR]

This paper presents a new application of logic programming to a real-life problem in hydraulic engineering. The work is developed as a collaboration of computer scientists and hydraulic engineers, and applies Constraint Logic Programming to solve a hard combinatorial problem. This application deals with one aspect of the design of a water distribution network, i.e., the valve isolation system design. We take the formulation of the problem by Giustolisi and Savić (2008 Optimal design of isolation valve system for water distribution networks. In Proceedings of the 10th Annual Water Distribution Systems Analysis Conference WDSA2008, J. Van Zyl, A. Ilemobade, and H. Jacobs, Eds.) and show how, thanks to constraint propagation, we can get better solutions than the best solution known in the literature for the Apulian distribution network. We believe that the area of the so-called hydroinformatics can benefit from the techniques developed in Constraint Logic Programming and possibly from other areas of logic programming, such as Answer Set Programming. [ABSTRACT FROM AUTHOR]