COVID-19: Agent-Based Simulation-Optimization to Vaccine Center Location Vaccine Allocation Problem

This paper presents an agent-based simulation-optimization modeling and algorithmic framework to determine the optimal vaccine center location and vaccine allocation strategies under budget constraints during an epidemic outbreak. Both simulation and optimization models incorporate population health dynamics, such as susceptible (S), vaccinated (V), infected (I) and recovered (R), while their integrated utilization focuses on the COVID-19 vaccine allocation challenges. We first formulate a dynamic location-allocation mixed-integer programming (MIP) model, which determines the optimal vaccination center locations and vaccines allocated to vaccination centers, pharmacies, and health centers in a multi-period setting in each region over a geographical location. We then extend the agent-based epidemiological simulation model of COVID-19 (Covasim) by adding new vaccination compartments representing people who take the first vaccine shot and the first two shots. The Covasim involves complex disease transmission contact networks, including households, schools, and workplaces, and demographics, such as age-based disease transmission parameters. We combine the extended Covasim with the vaccination center location-allocation MIP model into one single simulation-optimization framework, which works iteratively forward and backward in time to determine the optimal vaccine allocation under varying disease dynamics. The agent-based simulation captures the inherent uncertainty in disease progression and forecasts the refined number of susceptible individuals and infections for the current time period to be used as an input into the optimization. We calibrate, validate, and test our simulation-optimization vaccine allocation model using the COVID-19 data and vaccine distribution case study in New Jersey. The resulting insights support ongoing mass vaccination efforts to mitigate the impact of the pandemic on public health, while the simulation-optimization algorithmic framework could be generalized for other epidemics. [ FROM AUTHOR] Copyright of IISE Transactions is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)

A hybrid metaheuristic algorithm for the multi-objective location-routing problem in the early post-disaster stage

Disasters such as earthquakes, typhoons, floods and COVID-19 continue to threaten the lives of people in all countries. In order to cover the basic needs of the victims, emergency logistics should be implemented in time. Location-routing problem (LRP) tackles facility location problem and vehicle routing problem simultaneously to obtain the overall optimization. In response to the shortage of relief materials in the early post-disaster stage, a multi-objective model for the LRP considering fairness is constructed by evaluating the urgency coefficients of all demand points. The objectives are the lowest cost, delivery time and degree of dissatisfaction. Since LRP is a NP-hard problem, a hybrid metaheuristic algorithm of Discrete Particle Swarm Optimization (DPSO) and Harris Hawks Optimization (HHO) is designed to solve the model. In addition, three improvement strategies, namely elite-opposition learning, nonlinear escaping energy, multi-probability random walk, are introduced to enhance its execution efficiency. Finally, the effectiveness and performance of the LRP model and the hybrid metaheuristic algorithm are verified by a case study of COVID-19 in Wuhan. It demonstrates that the hybrid metaheuristic algorithm is more competitive with higher accuracy and the ability to jump out of the local optimum than other metaheuristic algorithms.

The smart city and COVID-19

Smart cities are concepts much loved by politicians and technologists but are very difficult to bring about in practice. There are many isolated applications in cities such as operating streetlamps, but very few, if any, examples of integrated applications sharing data and managing the city as a holistic entity rather than a set of disparate and unconnected applications. This is despite hundreds of trials and indicates how difficult bringing about a smart city will be. The key challenge is the wide range of interested parties in a city including the elected city authority, subcontractors and suppliers to the authority, emergency services, transport providers, businesses, residents, workers, tourists, and other visitors. Some of these entities will be primarily driven by finance, such as businesses and transport providers. Some will be driven by political considerations. Some will be concerned with the quality of life as well as financial costs. In some cases, there will be conflicting interests-the city may want as much information as possible on people in the city, whereas individuals may want privacy and the minimum data stored concerning their movements and attributes. COVID-19 does not change any of these issues, but it does increase the importance of some applications such as smart health, logistics, people surveillance, data security, and crisis management, while reducing the importance of others such as traffic management. It may result in more willingness for monitoring and data sharing if this can be shown to result in better control of the virus. © 2023 the authors.

The Relationship between Air Travel Service Quality and Factors of Theory of Planned Behavior: Evidence from Low-Cost Airlines in Thailand

Despite an increased emphasis on improvement in airline service quality concerning consumer behavior, such as passenger repurchasing as a result of their behavioral intention over the last several decades, there is still much less concern with the nature of airline service quality than should exist in the so-called "logistics service quality” and less concern with examining the specific behavioral intention preceding repurchasing behavior together with the theory of planned behavior. As such, this study aims to explore these issues, along with the psychological factors of the theory of planned behavior, that can lead to repurchasing behavior via word-of-mouth intention (WOMI). With an online survey of 383 respondents experienced with flying, the results reveal that the logistics service quality and each determinant in the theory positively influence a passenger's repurchasing behavior through WOMI. Accordingly, service marketers can implement service design and apply integrated marketing communication by learning from repurchasing behavior that was formed by the given factors to retain their existing customers. Moreover, this study is the first to empirically and explicitly validate dimensions of airline services through the lens of logistics that are deemed fit with the nature of the airlines. It advances the understanding of theory approaching and connects what has hampered its advancement in a body of knowledge, simultaneously in a context of airline context where it should not be relegated to transportation and consumer and service orientation.

Keeping Europe's Medicines Stocked

[...]best-in-class pharma companies are focusing on reliability and resilience in the supply chain-if they can't make a product or deliver a product on time, a patient is not served, and no sale is made. People can scale to a certain degree but scaling by a factor of 100 is not possible with people in a short period of time and does not deliver on economies of scale. Pharma companies are also issuing 'green bonds' where investors can expect the contribution of capital to improve the company's sustainability.

Cold Comfort for Bio/Pharma

The COVID-19 pandemic highlighted how vital cold chain is for the pharmaceutical industry, particularly as some vaccines needed to be produced, transported, and stored at -70 °C. Market projections for cold chain logistics of pharmaceuticals are projected to grow at a compound annual growth rate of 9.03% by 2025, which is reported to be driven by greater global demand for pharmaceuticals, increasing initiatives to promote cold chain, and more demand for reefer containers from the pharma industry (1). Gilmore (Tower Cold Chain): Putting the European success of the COVID-19 vaccine rollout to one side, the demand for effective temperature-controlled packaging solutions in the pharmaceutical supply chain has increased significantly in recent years. Today, the cold chain is grappling with additional challenges: serving a global market, driving out costs and waste, addressing capacity and resource constraints, and dealing with continually mounting regulations-all whilst handling valuable pharmaceutical cargo. Cold chain logistics providers must invest in the latest on-board equipment built into containers to track temperature and location, and to make data available to partners and customers in real time, to prevent or mitigate loss.

Intelligent Methods and Models for Assessing Level of Student Adaptation to Online Learning

The problem of introducing online learning is becoming more and more popular in our society. Due to COVID-19 and the war in Ukraine, there is an urgent need for the transition of educational institutions to online learning, so this paper will help people not make mistakes in the process and afterward. The paper's primary purpose is to investigate the effectiveness of machine learning tools that can solve the problem of assessing student adaptation to online learning. These tools include intelligent methods and models, such as classification techniques and neural networks. This work uses data from an online survey of students at different levels: school, college, and university. The survey consists of questions such as gender, age, level of education, whether the student is in the city, class duration, quality of Internet connection, government/non-government educational institution, availability of virtual learning environment, whether the student is familiar with IT, financial conditions, type of Internet connection, a device used for studying, etc. To obtain the results on the effectiveness of online education were used the following machine learning algorithms and models: Random Forest (RF), Extra Trees (ET), Extreme, Light, and Simple Gradient Boosting (GB), Decision Trees (DT), K-neighbors (K-mean), Logistic Regression (LR), Support Vector Machine (SVM), Naїve Bayes (NB) classifier and others. An intelligent neural network model (NNM) was built to address the main issue. © 2023 Copyright for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0). CEUR Workshop Proceedings (CEUR-WS.org)

Research on cold chain logistics optimization model considering low-carbon emissions

Cold chain logistics distribution orders have increased due to the impact of COVID-19. In view of the increasing difficulty of route optimization and the increase of carbon emissions in the process of cold chain logistics distribution, a mathematical model for route optimization of cold chain logistics distribution vehicles with minimum comprehensive cost is established by considering the cost of carbon emission intensity comprehensively in this paper. The main contributions of this paper are as follows: 1) An improved hybrid ant colony algorithm is proposed, which combined simulated annealing algorithm to get rid of the local optimal solution. 2) Chaotic mapping is introduced in pheromone update to accelerate convergence and improve search efficiency. The effectiveness of the proposed method in optimizing cold chain logistics distribution path and reducing costs is verified by simulation experiments and comparison with the existing classical algorithms. © 2023 The Author(s). Published by Oxford University Press.

Path Planning of Follow-up Transport Robot Based on Machine Vision

With the upgrading and innovation of the logistics industry, the requirements for the level of transportation smart technologies continue to increase. The outbreak of the COVID-19 has further promoted the development of unmanned transportation machines. Aimed at the requirements of intelligent following and automatic obstacle avoidance of mobile robots in dynamic and complex environments, this paper uses machine vision to realize the visual perception function, and studies the real-time path planning of robots in complicated environment. And this paper proposes the Dijkstra-ant colony optimization (ACO) fusion algorithm, the environment model is established by the link viewable method, the Dijkstra algorithm plans the initial path. The introduction of immune operators improves the ant colony algorithm to optimize the initial path. Finally, the simulation experiment proves that the fusion algorithm has good reliability in a dynamic environment. © 2022 IEEE.

Safeguarding Biologies-Blending Engineering Ingenuity and Managerial Excellence

Many best practices and lessons learned have emerged in recent years as pharma/life sciences companies, along with their third-party logistics partners and vendors that supply specialized packaging and monitoring solutions, have all weathered the COVID-19 pandemic together and continued to support ongoing growth in the pipeline of therapeutic products that must be continuously maintained at refrigerated, frozen, or ultra-frozen temperatures. Cold chain planning and execution "... continues to be impacted by not only the pandemic but by other factors, such as air cargo capacity being down, instability related to inflation, the Russia/Ukraine conflict, and more, but despite it all, you still have patients depending on what you're delivering," notes Rob Coyle, senior vice president, healthcare strategy, Kuehne+Nagel. "With careful planning, we're often able to replace active shippers with passive units by leveraging existing infrastructure, ongoing advances in insulation materials, phase-change materials (PCM), and container designs, using advanced GPS and other monitoring devices to ensure continuous access to real-time location, temperature, and other data," adds Scott Ohanesian, senior vice president, commercial operations, QuickStat, a Kuehne+Nagel company. Technology advances "The Holy Grail for the pharma cold chain is 'how do I get perfect service at a more economical price?'" says Dan Gagnon, vice president of global strategy for UPS Healthcare.

Track-and-Trace Progress Benefits Supply-Chain Security Efforts

COVID-19 vaccines, approved under emergency use authorization, were not required to meet serialization requirements, but they have been properly labelled to meet US Food and Drug Administration (FDA) requirements, he says, complete with 2D barcodes with GTIN, lot, and expiry date. The company decided to serialize its Diprovan anesthetic, a workhorse generic product, using radio frequency identification tags containing the four identifiers (2). "If an agent is handling your product on your behalf, they need to leverage GS1 Standards including GTINs for products [and] global location numbers (GLNs) for physical locations, and share data electronically using electronic product code information services (EPCIS) to capture events from manufacturing to serialization [and] capping to shipping.

Collaboration in humanitarian operations in the context of the COVID-19 pandemic

This chapter provides an overview of collaboration in humanitarian operations, focusing on the logistical aspects. Humanitarian logistics and operations has emerged as a subfield of supply chain and operations management and studies how humanitarian organizations can be more efficient in the delivery of humanitarian aid. We review the key characteristics of this subfield compared to traditional logistics and supply chain management. Collaboration is particularly important in the humanitarian context, in which only the collective performance of humanitarian organizations should count. We therefore discuss key factors of collaboration using the humanitarian SCOR model. Finally, we analyze how far the COVID-19 pandemic has forced humanitarian organizations to collaborate differently in their operations and what can be learned from it for the future of humanitarian operations. © Springer Nature Switzerland AG 2023. All rights reserved.

From Landlocked to Land-Linked: Kazakhstan as a Transport and Logistics Centre Within the Silk Road Economic Belt

Kazakhstan, being in the centre of the Eurasian continent, is a landlocked country that shares a border both with China and Russia. Since its independence in 1991, Kazakhstan has attempted to take advantage of its geographical location, by becoming a bridge between Europe and China. To achieve this goal, Kazakhstan has actively participated in the construction of the Silk Road Economic Belt (SREB) and joined the Asian Infrastructure Investment Bank (AIIB) as one of the founding countries. These activities have brought Kazakhstan not only the opportunity to become a transport and logistics hub but also to reduce its dependence on Russian infrastructure. In the light of the current war in Ukraine, the transportation of goods through the territory of Kazakhstan becomes more crucial to China as it can bypass Russia. Though the SREB has enabled Kazakhstan to export more resources and become more independent from Russian infrastructure, same time, China might become a threat to Kazakhstan's economic independence, as it will be more connected to the Chinese infrastructure. This chapter also shows that during the COVID-19 pandemic, China's economic policy in Kazakhstan is evolving. China now spends less on large infrastructure projects and focuses more on Kazakhstan's raw materials. This study aims to take a comprehensive look at Kazakhstan's relationship with China, as well as the implications of the SREB for Kazakhstan and its transport capacity. © The Editor(s) (if applicable) and The Author(s), under exclusive licence to Springer Nature Switzerland AG 2022.

Drivers of digital supply chain transformation in SMEs and large enterprises – a case of COVID-19 disruption risk

PurposeDigital transformation in supply chains (SCs) has emerged as one of the most effective ways to minimize SC disruption risks. Given the unprecedented impact of the COVID-19 pandemic on global SCs, this study aims to identify and provide empirical evidence about the drivers of digital SC transformation, considering the interactivity between environmental dynamism, technology, and organizational capabilities during the pandemic era.Design/methodology/approachUsing partial least squares structural equation modeling (PLS-SEM), this study examines 923 firms in Vietnam to ascertain the drivers of digital SC transformation between small- and medium-sized enterprises (SMEs) and large enterprises, based on the technology–organization–environment (TOE) as an overarching framework.FindingsThis study finds that greater digital SC transformation adoption could be achieved under the interactivity between the TOE components of firms' technological competencies, learning capabilities, and disruptions in socioeconomic environments due to the COVID-19 pandemic. Moreover, a multigroup analysis shows that the drivers of digital SC transformation differ between SMEs and large enterprises. SMEs were found to be more motivated by the COVID-19 disruption risk when adopting digital SC models.Originality/valueThis study represents an original and novel contribution from Vietnam as an emerging market to the literature on the impact of COVID-19 on the global value chain. Apart from the unique dataset at the firm level, the analysis of interactions between external and internal drivers of digital SC transformation could provide crucial managerial implications for SMEs to survive major disruptions, such as those caused by the COVID-19 pandemic.

The resilience factors of the agri-food supply chain: An integrative review of the literature in the context of the COVID-19 pandemic

Purpose: During the COVID-19 global pandemic, a very significant change has occurred in the demand for basic goods, resulting from the change in the consumer needs of the population in light of a large-scale health and economic crisis. This has revealed the true importance that the agri-food supply chains (ASC) have in the design of business strategies, especially at exceptional times, when the logistics process must be robust enough to continue to ensure the supply of products. In this context, the article presents a qualitative review of the academic literature, with the aim of extracting those factors that have the greatest influence on the degree of resilience of the ASC.Design/methodology: The methodology used is the integrative review of scientific publications, with a closer focus on those specialized in the supply chain, in order to perform a critical analysis and demonstrate theory based on the existing evidence. Both the document search and the content analysis abide by rigorous, explicit criteria.Findings: The bibliographic analysis reveals that there are at least three business strategies that can be considered critical factors in the degree of resilience of the ASCs. These three strategies are: a customer-oriented business awareness;distribution models based on proximity;and cooperative practices among the factors that make up the value chains.Originality/value: In such an important historical moment as the Coronavirus pandemic, it is very appropriate to look back in order to analyze all the scientific literature that could help us to better understand the current situation. It is even more important to do so in those areas of knowledge that do not yet have a consolidated academic trajectory, such as in the case of the resilience of supply chains.

Building Resilient Supply Chains with Information Systems: Key Lessons from Médecins Sans Frontières Logistique During the COVID-19 Crisis

This research aims to analyze the resilience of humanitarian supply chains, with a focus on the role of information systems, through a case study of Médecins Sans Frontières Logistique during the COVID-19 pandemic. The empirical research methodology is based on a qualitative study, which includes semi-structured interviews with key actors and operators from the Médecins Sans Frontières Logistique during the COVID-19 crisis in 2020 and 2021. The paper highlights the crucial and inherent role of information systems on each of the four dimensions of humanitarian supply chain resilience: reorganization capacity, collaboration, flexibility, and humanitarian culture. Drawing on recent theoretical works on supply chain resilience as well as empirical results, the paper underscores the importance of information systems and proposes a conceptual model of the relationship between humanitarian supply chain resilience and the role of information systems. The value of this research is linked to its empirical and qualitative study of a Non-Governmental Organization logistics operation during an international crisis, which contributes not only to the literature on resilience, but also provides guidance for managers to target their actions responsively and proactively to enhance resilience over time.. Copyright © 2023 by SCITEPRESS - Science and Technology Publications, Lda. Under CC license (CC BY-NC-ND 4.0)

Comparative Analysis of Linear Regression and Logistic Regression for the COVID-19 Detection from CT-Scans

The new emerging Coronavirus disease (COVID-19) is a pandemic disease due to its enormous infectious capability. Generally affecting the lungs, COVID-19 engenders fever, dry cough, and tiredness. However, some patients may not show symptoms. An imaging test, such as a chest X-ray or a chest CT scan, is therefore requested for reliable detection of this pneumonia type. Despite the decreasing trends both in the new and death reported cases, there is an extent need for quick, accurate, and inexpensive new methods for diagnosis. In this framework, we propose two machine learning (ML) algorithms: linear regression and logistic regression for effective COVID-19 detection in the abdominal Computed Tomography (CT) dataset. The ML methods proposed in this paper, effectively classify the data into COVID-19 and normal classes without recourse to image preprocessing or analysis. The effectiveness of these algorithms was shown through the use of the performance measures: accuracy, precision, recall, and F1-score. The best classification accuracy was obtained as 96% with logistic regression using the saga solver with no added penalty against 95.3% with linear regression. As for precision, recall, and F1-score the value of 0.89 was reached by logistic regression for all these metrics, as well as the value of 0.87 by linear regression. © 2022 IEEE.

Role of Logistics Integration Capability in Enhancing Performance in Omni-Channel Retailing: Supply Chain Integration as Mediator

Although the importance and benefits of logistics integration in omni-channel (OC) retailing have been discussed in the literature, the impacts of logistics integration from the dimension of internal and external logistics remain unknown. To fill this gap, this study aims to investigate the relationships among internal and external logistics integration capabilities, supply-chain integration (SCI), and financial performance (FP) in OC retailing based on the dynamic capability view. An empirical study is conducted based on a survey of 230 OC retailers in China's market. Factor analysis and regression analysis are conducted to examine the hypotheses of the proposed conceptual model. The quantitative analyses show that the internal logistics integration capability is significantly related to the external logistics integration capability, and they both have positive effects on SCI, while the external logistics integration capability generates a higher impact (i.e., almost 1.5 times that of the internal logistics integration capability). The numerical results also demonstrate that the logistics integration capabilities and SCI have similar positive effects on FP (i.e., all the relevant regression coefficients show values around 0.25), and SCI plays a partial intermediary role in the relationships between logistics integration capabilities and FP. Furthermore, the quantitative evidence addresses the fact that the FP is not influenced by OC retailers' characteristics, indicating a fair business environment in the OC retail industry.

Advancing Accessibility through Point-of-Use"j, Manufacturing

[...]it can be difficult to provide and ensure the same degree of quality, consistency, and compliance in a point-of-use facility compared to a centralized manufacturer. While you have possibly solved the issue of patient access and therapy transport, you have introduced logistical issues with maintaining supply chain and support (engineering, maintenance, calibration, etc.) logistics. The facility is intended to serve a local patient population instead of a global population. [...]the scale of production for a point-of-use facility is going to be smaller by design. The design team would need to account for the site location requirements, and, if the point-of-use facility is intended to be mobile and relocatable, the span of site requirements it may encounter.

Integration of RFID strategic value attributes mechanism decision in apparel supply chain: fuzzy AHP-TOPSIS approach

PurposeThe purpose of this paper is to identify the radio frequency identification (RFID) strategic value attributes (RFIDSVAs) mechanism selections preferences and also integration of RFID tags with technology coordination tools (IRTWTCTs) alternatives ranking performance decisions in supply chain management (SCM). RFID-enabled techno-economic feasibility decisions are enhancing the SC visibility in apparel supply chains (ASCs). The RFIDSVAs mechanism selections have performed significant agility to strategic competitive advantages, namely, inventory visibility, multi-tags ownership transfer within trusted third party, etc.Design/methodology/approachFuzzy analytical hierarchy process (FAHP) and FAHP-fuzzy Technique for Order of Preference by Similarity to Ideal Solution (FTOPSIS) approaches have been used to evaluate the quantitative assessment of RFIDSVA mechanisms selection decision based on weight priority orders and IRTWTCTs alternatives selection in ASC networks. The comparison of FAHP and FAHP-FTOPSIS approaches to evaluate the integrated framework develop in RFIDSVAs mechanisms and IRTWTCTs alternatives selection decisions in Indian multi-tier ASC networks.FindingsThe result found that the FAHP-FTOPSIS approaches have used to prioritizing the RFIDSVA mechanism selection weights and also identify the IRTWTCTs alternatives ranking preferences order in apparel SCM. The comparison between the FAHP and FAHP-FTOPSIS approach to quantitative assessments from RFIDSVA mechanisms and IRTWTCTs alternatives selection decisions, which enable them SC agility potential across multi-tier visibility in ASC networks. ASC stakeholders can be benefited by techno-economic feasibility decisions, RFID-enabled shop floor activities, multi-tags ownerships transfer in SCs and knowledge-based cryptography tags/items separation in SCs.Research limitations/implicationsThe research work has considered only five RFIDSVA mechanisms and also three integration of RFIDTWTCTs alternatives in multi-tier ASC. The strategic competitive advantages are achieved by RFID-enabled break-even tags price decisions and also techno-economic feasibility decision by contractual design multi-tier SC stakeholder's involvements.Practical implicationsThe pilot project study explores that the quantitative assessment decision has based on RFID-enable techno-economic feasibility in ASCs. Stakeholders can be benefited by inventory control of the financial losses, reducing the inventory inaccuracies and multi-tags ownership transfer within trusted third-party traceability in ASC networks.Originality/valueThis study explores the RFID-enabled apparel SC process and activities visibility (natural fibre's fibre producer, fibre dyeing producer, yarn spinning producer, knitting and finishing producer).