1,720,959 research outputs found
Innovative Applications of Unsupervised Learning in Uncertainty-Aware Pharmaceutical Supply Chain Planning
No full textThe significance of resiliency, reliability, and equity in the pharmaceutical supply chain is often overlooked but becomes evident in the wake of disastrous events. Disruptive incidents underscore the critical importance of these concepts, necessitating the development of innovative frameworks to effectively address the challenges that emerge in their aftermath. This paper introduces a framework specifically designed to address the issues arising from disruptions within the pharmaceutical supply chain. A novel mixed-integer nonlinear programming (MINLP) model is proposed to formulate the pharmaceutical supply chain that encompasses the distribution of both cold and non-cold pharmaceuticals and vaccines. The abundance of diverse pharmaceuticals and vaccines, each with its distinct characteristics, presents a formidable planning obstacle. A noteworthy contribution of this study lies in innovatively applying AI-driven methodologies to pharmaceutical supply chain, employing five pioneering unsupervised learning algorithms for improved inventory management and control. The model's uncertainty is effectively addressed through an innovative joint chance constraint (JCC) formulation. By employing JCC, the model ensures a high level of reliability in satisfying uncertain patient demands. The MINLP formulation with JCCs presents significant computational complexities and intractability. To alleviate these issues, state-of-the-art reformulation algorithms are provided to transform the model into its equivalent mixed-integer linear programming form. The results indicate the efficiency of the equivalent reformulation techniques and illustrate the capabilities of the model to alleviate the resiliency, reliability, and equity concerns
Distributed Artificial Intelligence Application in Agri-food Supply Chains 4.0
No full textSupply Chain 4.0 is characterized by various factors, including seamless integration and connectivity, the Internet of Things (IoT), Big Data, AI participation, Cyber-Physical Systems (CPSs), flexibility, adaptability, and customer-centricity across different parts of the supply chain. The application of Distributed AI (DAI) systems like Multi-Agent Systems (MAS) opens new horizons to enhance the efficiency, responsiveness, and intelligence of these supply chains. DAI facilitates advanced autonomous decision-making and real-time optimization at different stages of the agri-food supply chain, such as demand forecasting, inventory management, production planning, logistics optimization, and quality assurance and control. This article, by focusing on the case of scheduling through the entire supply chain, examines how DAI initiatives, including Multi-Agent Systems (MASs) enhanced with Case-Based Reasoning (CBR), enable the distribution of intelligence across smart, interconnected elements of the supply chain network. It is shown that through the use of DAI in SCM, the performance of the entire supply chain optimizes consistently and adaptively through the use of MAS, in which different parts of SCM collaborate as agents. Supply Chain 4.0 can gain autonomy, self-organization, self-optimization, self-adaptation, robustness, and flexibility, and its knowledge base can be enriched over time by using CBR to learn from past situations. It also discusses the opportunities and challenges associated with the adoption of DAI in Supply Chain 4.0, including operational efficiency, cost reduction, agility enhancement, and improved customer satisfaction. However, several concerns, such as data security, privacy issues, and interoperability, must be addressed
On-site workshop investment problem: A novel mathematical approach and solution procedure
Full text linkIn real-world construction sites, On-Site Workshops (OSW) are installed to accelerate construction activities and facilitate the material handling process. These temporary OSWs are cost-effective, leading to decreasing the material handling cost and project makespan, which indicates their important role as a part of a construction project. However, considering the OSW, which has not been addressed in the project scheduling problems, requires the construction site to have a space capacity constraint while considering the workshop size, availability level, and other project-related constraints. In the present work, by considering the OSWs, a real construction project scheduling problem is studied as a Multi-Mode On-Site Workshop Investment Problem with Tardiness (MOSWIPT) while finding the installation/dismantling time of the OSWs. Two new (linear) mathematical programming models are proposed for MOSWIPT. Next, due to the NP-hardness of the problem, an enhanced Genetic Algorithm (GA)-based metaheuristic with efficient problem-specific improvement rules as local search and effective crossover and mutation operators is proposed. Computational experiments show that the proposed method has solved most of the instances of the addressed problem to optimality and outperformed the existing metaheuristics, e.g., Simulated Annealing (SA) and Particle Swarm Optimization (PSO). Finally, conclusions and suggestions for future studies are stated
A comprehensive review on operating room scheduling and optimization
Full text linkThe growing number of publications on Operating Room Scheduling (ORS) in recent years reflects the rapid advancements in the field. This review aims to comprehensively analyze the historical developments and evolving trends in operating room scheduling by systematically examining the literature from 2000 to 2023. A multi-database search, including Scopus, Web of Science, PubMed, ProQuest and IEEE Xplore was employed to ensure the inclusion of key studies. This paper presents a review of the factors, descriptive fields, and key issues in operating room scheduling. It also focuses on optimization techniques and solution approaches for both deterministic and uncertain conditions. Special attention is given to real-world constraints, such as resource limitations, staff availability and patient variability which significantly impact scheduling. The review identifies that ORS research covers a broad spectrum of problems and solutions, with no singular research trend dominating the field. This indicates that researchers are tackling diverse challenges across various contexts. The final section outlines the significant pitfalls and proposes future research directions, including the integration of emerging technologies and sustainability considerations. This review is a valuable resource for researchers, practitioners, and academicians in healthcare operations and hospital management, offering insights into current practices and future opportunities for innovation in ORS
Multi-surgeon and priority-aware scheduling for operating rooms scheduling: a robust-based approach
Full text linkIn the realm of medical centre operations, Operating Room (OR) departments emerge as pivotal entities, given their substantial financial and social implications. A fundamental aspect of OR theatre management pertains to advance scheduling. Within this research, a novel robust-based modelling approach is developed to formulate the Operating Room Scheduling (ORS) under an open scheduling strategy, considering both the most optimistic and pessimistic scenarios for surgeries. This approach ensures that the total duration of surgeries in an OR adheres to both standard and the maximum allowable working hours, even when surgeries extend to their best-case and worst-case durations on a given day. Furthermore, the model accommodates surgeries involving multiple surgeons from diverse specialties. To minimise the cancellation rate of critical patient operations, the prioritisation of vital patients in the sequence of daily operations is incorporated. The study employs an efficient solution approach combining the use of Lagrangian Relaxation to derive relaxations, and Valid Inequalities (VIs) to strengthen the quality of relaxation. This approach aims to enhance computational efficiency and reduce processing time for the proposed model. To validate its practicality and effectiveness, the model is applied to a real-world case study. The research also encompasses sensitivity analyses, offering valuable managerial insights
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe 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
Variations on the Author
Full text link“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
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Dispelling the Myths Behind First-author Citation Counts
Full text linkWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
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