1,720,975 research outputs found
A two-stage stochastic programming approach for the reorganization of regional Blood Management Systems
No full textGeographical accessibility to upper secondary education: an Italian regional case study
No full textIn this paper, a spatial analysis is performed to measure students’ access to the upper secondary education system. Based on the definition of quantitative indicators, the adopted approach is applied to an Italian regional case by exploiting the capabilities of a GIS software and using census tracts’ level data. The obtained results highlight geographical patterns of inequalities in access among students and shed light on the least served areas. Further analysis shows that accessibility reflects the degree of urbanization within the study region and that geographical distances are actual barriers to rural students since they are not compensated for by either economic status or the availability of digital infrastructures. The study offers empirical grounds to inform the decision-making process toward equity-in-access oriented interventions. Longer-term actions, as the activation of new schools (network expansion), the activation of new programs (service expansion) or the redistribution of their supply among the current network (network reorganization), as well as mid-term ones, like offering economic support for students’ mobility, or reinforcing digital connectivity, emerge as relevant to mitigate social exclusion
Multi-echelon facility location models for the reorganization of the Blood Supply Chain at regional scale
No full textBlood and blood products are crucial resources requiring effective management strategies and policies due to the potential severe consequences that could arise from their lack. Over the past two decades, the global healthcare community has recognized the significance of managing the Blood Supply Chain (BSC) efficiently and effectively. This includes policy-making, system design and organization. In this context, the Italian Healthcare Ministry issued a decree aimed at improving the BSC efficiency at regional level while reducing costs by providing several indications and restrictions to be accounted for. To address the need for improved BSC system management and design, we propose a mathematical modeling framework that builds upon and extends multi-echelon facility location and scenario-based mathematical models coming from literature, integrating soft constraints to achieve system aims with a multi-objective viewpoint. The proposed modeling framework has been implemented in two different perspectives: case-based and scenario-based. These two perspectives approaches are conceived to provide a comprehensive solution to the issue at hand, performing sensitivity analysis, and enabling the design of an efficient and effective BSC at the regional level, capable of handling inherent system uncertainty. To this aim, the proposed modeling framework comprises several objectives, including minimizing transportation costs, rationalizing the number and type of facilities, ensuring self-sufficiency, guaranteeing an average accessibility threshold, satisfying imposed restrictions and system constraints, and designing a system robust to varying exogenous and endogenous conditions. Real-world data sets were utilized to test and validate the proposed formulations. The obtained results demonstrate that they can be a valuable decision support tool for decision-makers, providing managerial insights and enabling the simulation of different system configurations
Towards a stochastic programming modeling framework for districting
No full textIn this paper a stochastic districting problem is investigated. Demand is assumed to be represented by a random vector with a given joint probability distribution function. A two-stage mixed-integer stochastic programming model is proposed. The first stage comprises the decision about the initial territory design: the districts are defined and all the territory units assigned to one and exactly one of them. In the second stage, i.e., after demand becomes known, balancing requirements are to be met. This is ensured by means of two recourse actions: outsourcing and reassignment of territory units. The objective function accounts for the total expected cost that includes the cost for the first-stage territory design plus the expected cost incurred at the second stage by outsourcing and reassignment. The (re)assignment costs are associated with the distances between territory units, i.e., the focus is put on the compactness of the solution. The model is then extended in different ways to account for aspects of practical relevance such as a maximum desirable dispersion, reallocation constraints, or similarity of the second-stage solution w.r.t. the first-stage one. The new modeling framework proposed is tested computationally using instances built using real geographical data
Going Beyond Counting First Authors in Author Co-citation Analysis
Get PDFThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
An optimization model for the outbound truck scheduling problem at cross-docking platforms
No full text© 2017, Springer International Publishing AG. A cross-dock is a facility where arriving materials are sorted, grouped and delivered to destinations, with very limited storage times, with the overall objective of optimizing the total management costs. The operational efficiency of a cross-docking system strongly depends on how the logistic activities are organized. For this reason, optimization models and methods can be very useful to improve the system performances. In this paper, we propose a mathematical model to describe the so-called truck scheduling problem at a cross-docking platform. The model considers most of the actual constraints occurring in real problems; therefore, it can be viewed as an interesting basis to define a decision support system for this kind of problems. Some preliminary results show that the model can be efficiently solved in limited computational times
Variations on the Author
Get PDF“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Multi-stage stochastic districting: optimization models and solution algorithms
Get PDFThis paper investigates a Multi-Stage Stochastic Districting Problem (MSSDP). The goal is to devise a districting plan (i.e., clusters of Territorial Units—TUs) accounting for uncertain parameters changing over a discrete multi-period planning horizon. The problem is cast as a multi-stage stochastic programming problem. It is assumed that uncertainty can be captured by a finite set of scenarios, which induces a scenario tree. Each node in the tree corresponds to the realization of all the stochastic parameters from the root node—the state of nature—up to that node. A mathematical programming model is proposed that embeds redistricting recourse decisions and other recourse actions to ensure that the districts are balanced regarding their activity. The model is tested on instances generated using literature data containing real geographical data. The results demonstrate the relevance of hedging against uncertainty in multi-period districting. Since the model is challenging to tackle using a general-purpose solver, a heuristic algorithm is proposed based on a restricted model. The computational results obtained give evidence that the approximate algorithm can produce high-quality feasible solutions within acceptable computation times
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