Logistical Problems Research Articles

PUBLIC ADMINISTRATION POLICY IN THE HEALTHCARE SECTOR UNDER MARTIAL LAW

The article analyzes the main directions of public administration in the field of health care of Ukraine during martial law. The main focus is on the adaptation of the legislative framework and the modernization of management approaches, which allow to ensure the effective functioning of the health care system in crisis situations. The issue of creating mobile medical teams and hospitals, which are the main tool for providing medical care in front-line and de-occupied areas, was considered. The contribution of international organizations to the support of the Ukrainian medical system in terms of supplying medical equipment, medicines and providing financial assistance is analyzed. The key normative legal acts, which were adopted from 2022 and contributed to the adaptation of the medical system to new challenges, were studied. Features of the functioning of the Resolution of the Cabinet of Ministers No. 302, No. 683, No. 1078 and others are given. Particular attention is paid to the digitization of health care, the implementation of electronic medical records in order to ensure the prompt provision of medical services. The problems of medical institutions in the front-line zones, including the destruction of more than 700 hospitals, and ways to solve the logistical problems of the supply of medicines were considered. A conclusion was made regarding the further development of public administration in the field of health care based on the integration of international and national resources, improvement of digital technologies and modernization of medical infrastructure. Ensuring adequate funding of the health care system, which includes the health insurance program, emergency and specialized medical care, is revealed, which is a priority in the 2023 budget. The article examines the influence of international humanitarian organizations on the support of the Ukrainian health care system in the conditions of military operations. The basis for the development of long-term strategies for the recovery of medical facilities after destruction and their equipment with modern technologies is proposed. Aspects of integration of digital solutions to ensure the continuity of medical services in the most difficult conditions have been studied.

Research on cargo volume prediction and personnel scheduling optimization of sorting center based on BP neural network and improved genetic algorithm

With the development of Internet technology, e-commerce has become the primary choice for consumers to shop, and the huge order transaction volume has generated logistics problems. As an important part of the logistics network, the sorting platform is essential to improve its management efficiency. To enhance the efficiency of the sorting center, the topological relationship diagram is used to show the logistics network, and the cargo volume of the sorting center in the next 30 days and every hour is predicted based on the BP neural network model. Based on the mixed integer linear programming model and the improved genetic algorithm SCAGA model, the total man-days are minimized to ensure that the cargo volume is processed. At the same time, to ensure that the actual hourly efficiency is as balanced as possible, the optimization problem of personnel scheduling is studied. To maintain the efficient operation of the logistics industry, the accurate prediction of the number of goods and the reasonable scheduling of personnel, to provide a set of efficient and economical personnel scheduling programs for the logistics company, thus improving the overall operational efficiency and service quality.

Exact methods for the Selective Assessment Routing Problem

AbstractThe Selective Assessment Routing Problem (SARP) is a problem in humanitarian logistics addressing the site selection and routing decisions of rapid needs assessment teams which aim to evaluate the post-disaster conditions of different community groups, each carrying a distinct characteristic. The aim is to construct an assessment plan that maximizes the covering of different characteristics in a balanced way. We explore exact approaches based on mixed integer linear programming. Different mathematical formulations are presented, and theoretical results regarding their strengths are derived. The models are experimentally evaluated on a set of test instances including a real-world scenario.

Reducing ACO Population Size to Increase Computational Speed

Ant Colony Optimization (ACO) is a powerful metaheuristic algorithm widely used to solve complex optimization problems in production and logistics. This paper presents a methodology for enhancing the ACO performance when applied to Traveling Salesman Problems (TSP). By reducing the number of ants in the colony, the algorithm's computational speed improves but solution quality is sacrificed. An optimal number of ants to produce the best results in the shortest time is specific to the problem at hand and can't be defined generally. This paper investigates the effect of ant population reduction relative to the problem size by measuring its impact on solution quality and execution time. Results show that for certain problem sizes ant population and execution time can be halved with practically no reduction in solution quality, or they can be reduced 5 times at the price of slightly worse solution quality. Reduction of ant population is much more impactful on reduction of execution time than it is on solution quality.

The Role of Micro Fulfilment Centers in Alleviating, in a Sustainable Way, the Urban Last Mile Logistics Problem: A Systematic Literature Review

This systematic literature review has as its aim to discuss how the use of micro fulfilment centers can help logistics and supply chain professionals in alleviating the urban last mile logistics problem. This systematic literature review adapts the SALSA approach, the PRISMA 2009 checklist, and the PRISMA 2020 flow diagram, while its validity is based on the utilization of the qualitative CASP checklist. In addition to the above, certain inclusion/exclusion criteria were used. The findings of this review underline that micro fulfilment centers are a key new approach in terms of alleviating the last mile logistics problem, in urban areas where space is extremely limited via a reduction in CO2 emissions, the use of new technologies not only in operations but also in the delivery of goods and the increase in customer satisfaction. This is an original and breakthrough literature review as it covers a gap in the existing literature that has to do with the role of micro fulfilment centers in urban areas in terms of alleviating the last mile logistics problem, a topic about which not much have been written until now as it is quite novel. This literature review gives a clear path for the researcher of the future in terms of approaching the urban last mile logistics problem via the lens of the use of micro fulfilment centers, while it contributes to the urban logistics industry in several ways.

Parabolic logistic equation with harvesting involving the fractional Laplacian

This paper deals with a class of parabolic reaction-diffusion equations driven by the fractional Laplacian as the diffusion operator over a bounded domain with zero Dirichlet external condition. Using a comparison principle and monotone iteration method, we establish existence and uniqueness results. We apply the existence result to the logistic growth problems with constant yield harvesting by constructing an ordered pair of positive sub- and supersolution of the corresponding elliptic problem.

BLOCKCHAIN AND ITS APPLICATION IN THE DEFENCE SECTOR

The digital transformation of the economy affects many sectors, including the defence sector, which is sensitive from both a national and international perspective. The digitalisation of the economy is based on technologies such as robotics, autonomy, additive manufacturing technologies (3D printing), augmented reality, big data, quantum computers, artificial intelligence and blockchains. In this article, we will take a closer look at the latter, namely blockchain technology. We will briefly outline its main properties and advantages, which make it particularly attractive for use in the defence sector, and dwell on its application to implement such a tool as smart contracts. One of the key advantages of blockchain in the context of military operations is ensuring transparency and traceability of supplies. In today's realities, logistical problems can cost lives, but blockchain helps prevent fraud and improve coordination between interacting communication nodes. Thanks to the use of blockchain technologies, each unit of supply can be recorded in an immutable register, which allows you to track its path from sender to recipient. This reduces the risk of loss or theft, and simplifies the process of monitoring and verifying the accuracy of information about deliveries. In addition, the decentralised nature of the blockchain enhances the security of military communications, protecting them from interception and attack. Each message is encrypted in such a way that it can only be read by the addressee. This ensures a high level of confidentiality and data protection, as information transmitted through the blockchain is distributed among numerous network nodes, making it difficult for attackers to access. By using cryptographic methods, the blockchain ensures that even in the event of a successful attack, attackers will not be able to alter or falsify information. Creating a tamper-proof ID system will help fight counterfeiting and improve the process of identifying wounded or fallen soldiers. By assigning unique and unchangeable authenticators to personnel, equipment or weapons, one hundred per cent identification of military entities can be ensured. This allows for accurate tracking of the movement and status of each soldier and equipment, which contributes to more efficient resource management. This system also increases the level of trust in the information provided, as it is recorded in the blockchain and cannot be changed or deleted. The introduction of blockchain technology in the defence sector can bring significant benefits, including increased security, transparency and efficiency. However, this process is accompanied by numerous challenges and risks that need to be considered and overcome for successful integration.

Stage-Specific Multi-Objective Five-Element Cycle Optimization Algorithm in Green Vehicle-Routing Problem with Symmetric Distance Matrix: Balancing Carbon Emissions and Customer Satisfaction

This study presents a bi-objective optimization model for the Green Vehicle-Routing Problem in cold chain logistics, with a focus on symmetric distance matrices, aiming to minimize total costs, including carbon emissions, while maximizing customer satisfaction. To address this complex challenge, we developed a Stage-Specific Multi-Objective Five-Element Cycle Optimization algorithm (MOFECO-SS), which dynamically adjusts optimization strategies across different stages of the process, thereby enhancing overall efficiency. Extensive comparative analyses with existing algorithms demonstrate that MOFECO-SS consistently outperforms in solving the multi-objective optimization model, particularly in reducing total costs and carbon emissions while maintaining high levels of customer satisfaction. The symmetric nature of the distance matrix further aids in achieving balanced and optimized route planning. The results highlight that MOFECO-SS offers decision-makers flexible route planning options that balance cost efficiency with environmental sustainability, ultimately improving the effectiveness of cold chain logistics operations.

The Multi-Country Multi-City Collaborative Research Network: An international research consortium investigating environment, climate, and health.

Research on the health risks of environmental factors and climate change requires epidemiological evidence on associated health risks at a global scale. Multi-center studies offer an excellent framework for this purpose, but they present various methodological and logistical problems. This contribution illustrates the experience of the Multi-Country Multi-City Collaborative Research Network, an international collaboration working on a global research program on the associations between environmental stressors, climate, and health in a multi-center setting. The article illustrates the collaborative scheme based on mutual contribution and data and method sharing, describes the collection of a huge multi-location database, summarizes published research findings and future plans, and discusses advantages and limitations. The Multi-Country Multi-City represents an example of a collaborative research framework that has greatly contributed to advance knowledge on the health impacts of climate change and other environmental factors and can be replicated to address other research questions across various research fields.

Experiences of Dual Enrollment: Wisconsin Student Reflections on Its Role in Shaping Their Thinking of Their Educational Trajectory

Research indicates that engaging in dual enrollment (DE) courses positively impacts college performance and degree completion time, evidenced mostly by static outcome measures (e.g., success in college, college admission, grades). These indicators are important, but do not fully examine how students perceive/experience DE opportunities. The current study used focus groups with DE students across Wisconsin (N=49) to explore how they thought about their experiences and how it informed their thinking about their future educational trajectories. Five themes emerged from thematic analysis of focus groups. First, they were able to maximize their experience thanks to onboarding support. Second, they gave a general description of how they saw their own growth as learners. Third, throughout their in-person interactions on campus, DE had the biggest influence on how this individual understood themselves. Fourth, logistical problems made the experiences less enjoyable. Fifth, the fact that DE credits offered faster and less expensive routes to and through college served as a motivator for many. Student responses indicated that DE courses on college campuses, rather than high schools, yielded more benefits. Overall, the study points toward the value of exploring student experience and particularly in relation to modality of DE.

Solving the green reverse logistics problem in e-commerce using a reinforcement learning based genetic algorithm

This study explores the two-phase green reverse logistics problem with time windows and a focus on perishable items that pose a significant challenge in the management of returned goods in e-commerce. We proposed a mixed integer programming model that considers carbon emissions, fuel consumption costs, facility establishment and operating costs, among other factors.We incorporated reinforcement learning concepts to adjust parameters in traditional genetic algorithms, which often have inflexible parameter settings, thereby enhancing both the efficiency and quality of the solutions. The Q-learning algorithm was adopted as the learning method, and various action combinations of reinforcement learning were explored and compared. We further evaluated the performance of different genetic algorithm variations. The results indicate that the proposed algorithm provides high-quality solutions, and that effective parameter configuration significantly impacts the algorithm’s overall performance.

An integrated method to identify and improve logistical gaps

ABSTRACT This paper reviews the critical elements of the SCOR model and its applications in solving logistical problems. It also discusses the theoretical approach to BSC concepts and the analysis of the tactical scenario and a company’s restrictions. The study is inductive, validating theoretical aspects that can be generalised through empirical testing. The proposed methodology integrates the BSC and SCOR models, aligning operational and strategic indicators, to performance measurement and achieving profitability objectives. The model integrated suppliers, improving inventory management and productivity, and its structure is defined from the company’s main decisions related to supply chain processes. The SCOR and Balanced Scorecard models were tested in a logistic process in a hardware store, with no known background in the literature on its application in this industry. These two models were integrated into a unified tool, with an indicator dashboard as an output, to support decision-making at both strategic and operational (logistics) levels.

Many-Objective Simulation Optimization for Camp Location Problems in Humanitarian Logistics

Many-Objective Simulation Optimization for Camp Location Problems in Humanitarian Logistics

Global Fight against Malaria: Goals and Achievements 1900–2022

This article examines the historical and ongoing efforts to fight malaria, a parasitic disease caused by Plasmodium species and transmitted by Anopheles mosquitoes. Despite over a century of control efforts, malaria remains a major global health issue. In 2022, there were an estimated 249 million cases across 85 countries, leading to approximately 600,000 deaths. In the recently published Global Technical Strategy for Malaria 2016–2030, the World Health Organization (WHO) has prioritized malaria eradication. The main goals are to reduce malaria incidence and mortality by 90% by 2030 compared to 2015 levels. However, as of 2022, progress has been limited, with only a 2% reduction in incidence and a 6% reduction in mortality. This review traces the historical context of malaria, highlighting its ancient origins and the pivotal scientific discoveries in the late 19th century that paved the way for modern control measures. The Global Malaria Eradication Programme launched by the WHO in 1955 initially showed promise, largely due to the insecticide DDT, but ultimately failed to achieve its goals mainly due to logistical problems, vector resistance to DDT, and inadequate funding. Despite significant advances in the early 21st century, including the Roll Back Malaria initiative and increased international funding, malaria eradication remains a distant goal. Persistent challenges, such as weak healthcare systems, parasite and vector resistance to drugs and insecticides, and inadequate funding, continue to hamper global efforts. Therefore, this article underscores the need for a deeper understanding of malaria’s history and recent evolution to inform future strategies for eradication.

An artificial bee colony optimization algorithms for solving fuzzy capacitated logistic distribution center problem

This paper presents a methodological approach to solving the fuzzy capacitated logistic distribution center problem, with a focus on the optimal selection of distribution centers to meet the demands of multiple plants. The distribution centers are characterized by fixed costs and capacities, while plant demands are modeled using fuzzy triangular membership functions. The problem is mathematically formulated by converting fuzzy demands into crisp values, providing a structured framework for addressing uncertainty in logistic planning. To support future research and facilitate comparative analysis, 20 benchmark problems were generated, filling a gap in the existing literature. Three distinct artificial bee colony algorithm variants were hybridized with a heuristic: one using the best solution per iteration, another incorporating chaotic mapping and adaptive procedures, and the third employing convergence and diversity archives. An experimental design based on Taguchi's orthogonal arrays was employed for optimizing the algorithm parameters, ensuring systematic exploration of the solution space. The developed methods offer a comprehensive toolkit for addressing complex, uncertain demands in logistic distribution, with code provided for reproducibility.Key contributions include:•Development of a fuzzy model for the selection of distribution centers with fixed costs and capacities under uncertain plant demands.•Generation of 20 benchmark problems to advance research in the fuzzy capacitated logistic distribution center problem domain.•Integration of a heuristic approach with three distinct ABC algorithm variants, each contributing unique methodological insights.

Vehicle routing Problem for cold chain logistics based on data fusion technology to predict travel time

Vehicle routing Problem for cold chain logistics based on data fusion technology to predict travel time

Urban Sharing Logistics Strategies against Epidemic Outbreaks: Its Feasibility and Sustainability

Epidemic (e.g., COVID-19) outbreaks can seriously disrupt logistics, and the coordination of intercity logistics and urban distribution plays an important role in goods distribution. In previous studies, some scholars analyzed different sharing logistics mechanisms for cost reduction and efficiency improvement, while others analyzed the disruption problems in both logistics and supply chain management. In this study, we combine these two operational management philosophies and first develop a two-echelon logistics benchmark model (BM), with two intercity logistics companies and two urban distribution companies, taking into consideration the load ratio and the disruption factor. This is the first time that the load ratio is considered in research on logistics, and it will make the supply and demand as well as the cost structure of logistics services much more practical. We then develop three urban sharing logistics models with two intercity logistics companies and one urban sharing logistics distribution company, with the sharing mechanisms SM1 (only sharing logistics), SM2 (sharing logistics with revenue sharing), and SM3 (sharing logistics with equity investment). We compare the pros and cons of the three sharing mechanisms and identify the optimal and suboptimal Pareto improvements for the BM. We identify different sharing decisions with respect to different load ratios and the disruption ratio. Finally, we analyze the sustainability of the three sharing mechanisms from the load ratio, low-carbon, and low-disruption dimensions. The managerial implications drawn from the model and case study provide a practice framework for sharing logistics operations: vertical integration, the standardization of logistics technology and equipment, and coordination and sharing.

Harnessing the Power of Optimization: Vehicle Routing Problems in Logistics and Distribution

Harnessing the Power of Optimization: Vehicle Routing Problems in Logistics and Distribution

Audiophonologopedic Telerehabilitation: Advantages and Disadvantages from User Perspectives.

Technological advancements and the COVID-19 pandemic have highlighted the importance of digital tools for patient care and rehabilitation. This study explores user perspectives on telerehabilitation, comparing it to traditional methods and identifying criteria for determining its suitability for different patients and clinical conditions. This study was carried out during the period of May-September 2021. Questionnaires were administered to 48 users in rehabilitation for audiophonologopedic and neurodevelopmental disorders in three rehabilitation centres in central Italy. The user responses predominantly emphasize the benefits of time saving (68.75%) and cost-efficiency (37.5%), specifically regarding time saving due to travel and expenses incurred to go to where the therapy is carried out. The disadvantages include increased distraction (60.42%) in following the instructions remotely and logistic problems (39.58%). Patients with hearing loss were subjected to a larger number of telerehabilitation sessions, positively rating this alternative method. Patients with speech and language delay and autism spectrum disorder (ASD) prefer traditional treatment. This study reveals a favourable perception of telerehabilitation as a therapy approach to be regarded as a supplement or temporary option to the irreplaceable face-to-face one. More research, as well as a larger sample sizes, will be useful to increase the significance of the correlations reported in this study.

Optimization of industrial-scale composting of dewatered pig slurry and olive mill waste using discarded tennis balls as an inert bulking agent

Material shortages in composting may pose limits or logistical problems in certain regions, which can be addressed with inert and reusable wastes. Very little research has been conducted on the subject of using alternative synthetic wastes as structuring agents to improve composting process parameters. The present work aimed to evaluate the use of used tennis balls (TB) as an inert bulking agent. Composting was carried out in an industrial composting plant with a ternary mixture of olive mill waste, the solid fraction of dewatered pig slurry, urban pruning residues, with the addition of TB as a synthetic bulking agent. Composting process parameters, monitored throughout the composting cycle, showed that TB significantly affected the thermal composting process parameters, with increases in operating temperatures, exothermic index, and mineralization of organic matter. Also, compost properties were seen to be of equal or superior quality at the end of the composting with addition of TB. These are the first experimental results testing the effect of a spherical synthetic reutilized product such as TB on composting processes, which was additionally carried out at an industrial scale, showing that using discarded materials such as used tennis balls can improve the efficiency and economy of composting.