Improving Quality and Efficiency in Home Health Care: an application of Constraint Logic Programming for the Ferrara NHS unit

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 in their home: this choice reduces costs for the community and gives better quality of life to patients. On the other hand, it introduces the combinatorial problem of assigning patients to the available nurses in order to maximize the quality of service, without having nurses travel for overly long distances. In this paper, we describe the problem as a practical application of Constraint Logic Programming. We first introduce the problem, as it is currently addressed by the nurses in the National Health Service (NHS) in Ferrara, a mid-sized city in the North of Italy. Currently, the nurses solve the problem by hand, and this introduces several inefficiencies in the schedules. We formalize the problem, obtained by interacting with the nurses in the NHS, into a Constraint Logic Programming model. In order to solve the problem efficiently, we implemented a new constraint that tackles with the routing part of the problem. We propose a declarative semantics for the new constraint, and an implementation based on an external solver

Locating and Sizing Electric Vehicle Chargers Considering Multiple Technologies

In order to foster electric vehicle (EV) adoption rates, the availability of a pervasive and efficient charging network is a crucial requirement. In this paper, we provide a decision support tool for helping policymakers to locate and size EV charging stations. We consider a multi-year planning horizon, taking into account different charging technologies and different time periods (day and night). Accounting for these features, we propose an optimization model that minimizes total investment costs while ensuring a predetermined adequate level of demand coverage. In particular, the setup of charging stations is optimized every year, allowing for an increase in the number of chargers installed at charging stations set up in previous years. We have developed a tailored heuristic algorithm for the resulting problem. We validated our algorithm using case study instances based on the village of Gardone Val Trompia (Italy), the city of Barcelona (Spain), and the country of Luxembourg. Despite the variability in the sizes of the considered instances, our algorithm consistently provided high-quality results in short computational times, when compared to a commercial MILP solver. Produced solutions achieved optimality gaps within 7.5% in less than 90 s, often achieving computational times of less than 5 s

An Enhanced Path Planner for Electric Vehicles Considering User-Defined Time Windows and Preferences

A number of decision support tools facilitating the use of Electric Vehicles (EVs) have been recently developed. Due to the EVs’ limited autonomy, routing and path planning are the main challenges treated in such tools. Specifically, determining at which Charging Stations (CSs) to stop, and how much the EV should charge at them is complex. This complexity is further compounded by the fact that charging times depend on the CS technology, the EV characteristics, and follow a nonlinear function. Considering these factors, we propose a path-planning methodology for EVs with user preferences, where charging is performed at public CSs. To achieve this, we introduce the Electric Vehicle Shortest Path Problem with time windows and user preferences (EVSPPWP) and propose an efficient heuristic algorithm for it. Given an origin and a destination, the algorithm prioritizes CSs close to Points of Interest (POIs) that match user inputted preferences, and user-defined time windows are considered for activities such as lunch and spending the night at hotels. The algorithm produces flexible solutions by considering clusters of charging points (CPs) as separate CSs. Furthermore, the algorithm yields resilient paths by ensuring that recommended paths have a minimum number of CSs in their vicinity. The main contributions of our methodology are the following: modeling user-defined time windows, including user-defined weights for different POI categories, creating CSs based on clusters of CPs with sufficient proximity, using resilient paths, and proposing an efficient algorithm for solving the EVSPPWP. To facilitate the use of our methodology, the algorithm was integrated into a web interface. We demonstrate the use of the web interface, giving usage examples and comparing different settings

Perspective Chapter: Teaching Intuition and Creativity - An Interdisciplinary and Playful Approach

The students attending the Italian technical and vocational high schools have often a critical behavior towards the classes of Mathematics and Italian. They usually believe that these disciplines are sterile and marginal with respect to their main interests that rely on subjects characterizing their professional choice. We made some experiments intended to wake up the interest and reactivate the lost creativity in these two disciplines. We report on an interdisciplinary experience in the first-year class of a technical high school where we introduced a series of games in the classes of Mathematics and Italian, with the intent of stimulating creativity and empowering the students. In Maths, we applied the puzzle-based learning technique. In Italian, we used the creative writing technique. Despite the limited time devoted to this experience, the outcomes have been extremely positive

Designing Optimal Routes for Cycle-tourists

AbstractBicycles are becoming an increasingly popular mean of transport. Being healthy and affordable, they provide a sustainable alternative way of movement, for both leisure and work commuting. In both cases demand increases when bike devoted tracks are available. Providing bike trails that connect touristic spots is a cheap way of increasing the appeal and promoting the development of those regions featuring beautiful landscapes, strong cultural traditions, and historical monuments within a small area. This is the case of the Trebon region, South Bohemia, whose local administrators face the problem of optimally investing scarce resources to set up a network of cycle-dedicated tracks, exploiting existing trails or by reconstruction works, turning gravel roads or unsurfaced forest tracks into paved bike trails. As a first step, we address the design of a single route, modeled as a path on a directed graph between two given nodes, maximizing a utility function related to the attractiveness of the path. Attractiveness depends on several features, such as a service facility, a restaurant serving typical food, an historical village, or a scenic landscape to be enjoyed along the way. Two kinds of resource constraints bound the solution. A path maximum duration, which depends on how many times each arc is traversed, and a maximum budget for setting up the infrastructure, which depends on which arcs are selected. Since a cyclist may be willing to traverse an edge more than once - think, for example, of a detour from the main way to be travelled back and forth to reach a point of interest – cycles can be part of the route. The attractiveness function is concave and decreases after reaching its maximum at a few traversals. Such features make the problem new and challenging. We present an integer linear programming model and validate it by an experimental campaign on realistic data for the Trebon region

Cycle-tourist network design

Among the most effective actions to promote functional cycling, i.e., cycling as a mean of transport, infrastructure design and planning are major topics. Much less attention has been dedicated to the design and deployment of bikeways devoted to recreational cycling, despite the role of cycle routes in promoting cycle tourism, and the effectiveness of cycle tourism in fostering sustainable and environmentally friendly economic growth, in addition to encouraging healthy life styles. In this paper we contribute to fill this gap: we propose a quantitative based methodology for designing a cycle-tourist network infrastructure intended to provide local administrators with a quantitative based decision support tool to optimally exploit the scarce public funding devoted to the project deployment. We consider as a case study the data of the Trebon region, in South Bohemia. Given the local points of attractions and a set of potential links which can be turned into cycle pathways against a little investment in addition to a set of links already fit for cyclists, a network of cycle routes that interconnects a set of pre selected gates must be designed, so that the total link refurbishment cost is budget compliant and the attractiveness of cycle itineraries from gate to gate supported by the infrastructure is maximized. In previous studies we showed how to compute a resource-constrained optimal path from origin to destination, which maximizes a utility function related to the attractiveness of the arcs and nodes along the path. In a later work we generalized the problem to the case of multiple users with different utility functions that must share the same monetary budget. Building on these results, in this paper we propose a heuristic solution approach for the network design problem, where routes connecting several origin destination pairs have to be designed, yielding a connected infrastructure which allows for further itineraries. We exploit the ability of modern solvers to quickly find solutions to the single-pair single-user aforementioned case to generate a pool of promising paths from gate to gate, according to different preferences and constraints. In a second step, the network is built by solving a second combinatorial optimization problem which selects a path for each pair of gates from the pool, to yield a budget compliant connected infrastructure. Finally, a post optimization step deletes redundant links, if any. The solution approach is validated by an experimental campaign performed on realistic data for the Trebon zone, in Southern Bohemia

The Quadratic Shortest Path Problem:Complexity, Approximability, and Solution Methods

We consider the problem of finding a shortest path in a directed graph with a quadratic objective function (the QSPP). We show that the QSPP cannot be approximated unless P=NP . For the case of a convex objective function, an n-approximation algorithm is presented, where n is the number of nodes in the graph, and APX-hardness is shown. Furthermore, we prove that even if only adjacent arcs play a part in the quadratic objective function, the problem still cannot be approximated unless P=NP. In order to solve the problem we first propose a mixed integer programming formulation, and then devise an efficient exact Branch-and-Bound algorithm for the general QSPP, where lower bounds are computed by considering a reformulation scheme that is solvable through a number of minimum cost flow problems. In our computational experiments we solve to optimality different classes of instances with up to 1000 nodes

Designing the master schedule for demand-adaptive transit systems

Abstract Demand-Adaptive Systems (DAS) display features of both traditional fixed-line bus services and purely on-demand systems such as dial-a-ride, that is they offer demand-responsive services within the framework of traditional scheduled bus transportation. A DAS bus line serves, on one hand, a given set of compulsory stops according to a predefined schedule specifying the time windows associated with each, providing the traditional use of the transit line, without requiring any reservation. On the other hand, passengers may also issue requests for transportation between two desired, optional, stops, which induces detours in the vehicle routes. The design of a DAS line is a complex planning operation that requires to determine not only its design in terms of selecting the compulsory stops, but also its master schedule in terms of the time windows associated with the compulsory stops. Designing a DAS thus combines elements of strategic and tactical planning. In this paper we focus on determining a master-schedule for a single DAS line. We propose a mathematical description and a solution framework based on the estimation of a number of statistical parameters of the demand and the DAS line service. Results of numerical experiments are also given and analyzed

Electron-Beam-Induced Grafting of Chitosan onto HDPE/ATZ Composites for Biomedical Applications

The surface functionalisation of high-density polyethylene (HDPE) and HDPE/alumina-toughened zirconia (ATZ) surfaces with chitosan via electron-beam (EB) irradiation technique was exploited for preparing materials suitable for biomedical purposes. ATR–FTIR analysis and wettability measurements were employed for monitoring the surface changes after both irradiation and chitosan grafting reaction. Interestingly, the presence of ATZ loadings beyond 2 wt% influenced both the EB irradiation process and the chitosan functionalisation reaction, decreasing the oxidation of the surface and the chitosan grafting. The EB irradiation induced an increase in Young’s modulus and a decrease in the elongation at the break of all analysed systems, whereas the tensile strength was not affected in a relevant way. Biological assays indicated that electrostatic interactions between the negative charges of the surface of cell membranes and the –NH3+ sites on chitosan chains promoted cell adhesion, while some oxidised species produced during the irradiation process are thought to cause a detrimental effect on the cell viability

Mechanical and Biological Characterization of PMMA/Al2O3 Composites for Dental Implant Abutments

The mechanical and biological behaviors of PMMA/Al2O3 composites incorporating 30 wt.%, 40 wt.%, and 50 wt.% of Al2O3 were thoroughly characterized as regards to their possible application in implant-supported prostheses. The Al2O3 particles accounted for an increase in the flexural modulus of PMMA. The highest value was recorded for the composite containing 40 wt.% Al2O3 (4.50 GPa), which was about 18% higher than that of its unfilled counterpart (3.86 GPa). The Al2O3 particles caused a decrease in the flexural strength of the composites, due to the presence of filler aggregates and voids, though it was still satisfactory for the intended application. The roughness (Ra) and water contact angle had the same trend, ranging from 1.94 microns and 77.2° for unfilled PMMA to 2.45 microns and 105.8° for the composite containing the highest alumina loading, respectively, hence influencing both the protein adsorption and cell adhesion. No cytotoxic effects were found, confirming that all the specimens are biocompatible and capable of sustaining cell growth and proliferation, without remarkable differences at 24 and 48 h. Finally, Al2O3 was able to cause strong cell responses (cell orientation), thus guiding the tissue formation in contact with the composite itself and not enhancing its osteoconductive properties, supporting the PMMA composite’s usage in the envisaged application