Resource Allocation Process Research Articles

Machine Learning-Based Resource Allocation Strategy for Network Slicing in Vehicular Networks

The diversified service requirements in vehicular networks have stimulated the investigation to develop suitable technologies to satisfy the demands of vehicles. In this context, network slicing has been considered as one of the most promising architectural techniques to cater to the various strict service requirements. However, the unpredictability of the service traffic of each slice caused by the complex communication environments leads to a weak utilization of the allocated slicing resources. Thus, in this paper, we use Long Short-Term Memory- (LSTM-) based resource allocation to reduce the total system delay. Specially, we first formulated the radio resource allocation problem as a convex optimization problem to minimize system delay. Secondly, to further reduce delay, we design a Convolutional LSTM- (ConvLSTM-) based traffic prediction to predict traffic of complex slice services in vehicular networks, which is used in the resource allocation processing. And three types of traffic are considered, that is, SMS, phone, and web traffic. Finally, based on the predicted results, i.e., the traffic of each slice and user load distribution, we exploit the primal-dual interior-point method to explore the optimal slice weight of resources. Numerical results show that the average error rates of predicted SMS, phone, and web traffic are 25.0%, 12.4%, and 12.2%, respectively, and the total delay is significantly reduced, which verifies the accuracy of the traffic prediction and the effectiveness of the proposed strategy.

Structure Optimization of e-Commerce Platform Based on Artificial Intelligence and Blockchain Technology

The current e-commerce operation model has network defects such as network chaos and uneven network distribution, which affect economic development and progress. In response to the above problems, this article introduces the artificial intelligence system, optimizes and analyzes the structure of e-commerce websites, and combines the Internet economy with online website theory through independent screening and analysis of the artificial intelligence system. The concept of blockchain technology is introduced, and the characteristics of blockchain are analyzed through theory and data using quantitative analysis methods, and the problem of cross-border electronic payment is solved based on blockchain. Based on the analysis of artificial intelligence, an optimized online website innovation plan was obtained. Finally, the online website resource allocation variables are simulated, and the simulation method is used to test the scheme. The simulation test simulates the process of resource allocation, optimizes the use of innovative models, and hires professional financial personnel to observe records. The test verifies the effectiveness of the structure optimization of the e-commerce platform realized in this paper.

Application of greedy algorithms for the formation of the educational schedule in the higher education

The problem of improving the quality of the organization of the educational process in a higher educational institution (university) is solved by using greedy algorithms. This task is the main one in the activity of the dispatching service of each university. A well-prepared schedule should ensure a uniform load of student groups and faculty. A greedy algorithm is an algorithm consisting in making locally optimal decisions at each stage, assuming that the final solution also turns out to be optimal. A greedy resource allocation algorithm refers to an algorithm according to which the resource allocation process can be represented as a sequence of steps. At each step, an optimal distribution of some resources occurs under certain conditions, which does not change in the future. Numerous attempts to automate the process of forming the university curriculum did not solve the problem in full. Accordingly, in order to solve this problem more effectively, as well as reduce the time and money spent on resource allocation, it is necessary to optimize existing solutions. The purpose of this work is to develop an algorithm that will improve the quality of curriculum formation based on the use of greedy algorithms.

Формирование учебного расписания в вузе с применением жадных алгоритмов

A greedy resource allocation algorithm is understood as an algorithm according to which the resource allocation process can be represented as a sequence of steps. At each step, an optimal, under certain conditions, distribution of a part of the resources occurs, which does not change in the future. The problem of improving the quality of the organization of the educational process in a higher educational institution is solved on the basis of the use of greedy algorithms. A well-designed timetable should ensure an even workload of student groups and faculty. The purpose of this work is to develop an algorithm that can improve the quality of the formation of the educational schedule based on the use of greedy algorithms.

Optimal Renewable Resource Allocation and Load Scheduling of Resilient Communities

This paper presents a methodology for enhancing community resilience through optimal renewable resource allocation and load scheduling in order to minimize unserved load and thermal discomfort. The proposed control architecture distributes the computational effort and is easier to be scaled up than traditional centralized control. The decentralized control architecture consists of two layers: The community operator layer (COL) allocates the limited amount of renewable energy resource according to the power flexibility of each building. The building agent layer (BAL) addresses the optimal load scheduling problem for each building with the allowable load determined by the COL. Both layers are formulated as a model predictive control (MPC) based optimization. Simulation scenarios are designed to compare different combinations of building weighting methods and objective functions to provide guidance for real-world deployment by community and microgrid operators. The results indicate that the impact of power flexibility is more prominent than the weighting factor to the resource allocation process. Allocation based purely on occupancy status could lead to an increase of PV curtailment. Further, it is necessary for the building agent to have multi-objective optimization to minimize unserved load ratio and maximize comfort simultaneously.

El presupuesto maestro y los indicadores de control en el plan estratégico

El presente trabajo de investigación pretende analizar críticamente los enfoques y matices documentados en un intercambio dialógico con diferentes autores acerca de lautilidad del presupuesto maestro como herramienta para la asignación de fondos, pues éste establece dimensionesy medidas de manera anticipada al tener no solamente unenfoque contable, sino administrativo y financiero a la vez.Se entiende que los mecanismos de control administrativo son a su vez sistemas retroalimentadores para laplaneación y el control. Por el contrario, el presupuestomaestro es una herramienta que cumple los requisitos como indicador; que mide los procesos de la empresa. Puedealimentar cualitativa y cuantitativamente el proceso deasignación de fondos al acompañar, complementar y racionalizarla decisión de desembolso de capital. Indicar dondeexisten debilidades y fortalezas operativas, marcar eficiencias o anticipar ahorros en costos de manera que se asigneel efectivo disponible a las inversiones que cumplan con la política de rentabilidad y con productividad y eficiencia en el uso y aplicación de recursos. Por tanto, el presupuesto maestro es una herramienta útil en relación al diseño de estrategias y los sistemas de control, los objetivos inductores y el proceso de asignación de recursos.

Operational Recommendations for Scarce Resource Allocation in a Public Health Crisis

The coronavirus disease 2019 pandemic may require rationing of various medical resources if demand exceeds supply. Theoretical frameworks for resource allocation have provided much needed ethical guidance, but hospitals still need to address objective practicalities and legal vetting to operationalize scarce resource allocation schemata. To develop operational scarce resource allocation processes for public health catastrophes, including the coronavirus disease 2019 pandemic, five health systems in Maryland formed a consortium—with diverse expertise and representation—representing more than half of all hospitals in the state. Our efforts built on a prior statewide community engagement process that determined the values and moral reference points of citizens and health-care professionals regarding the allocation of ventilators during a public health catastrophe. Through a partnership of health systems, we developed a scarce resource allocation framework informed by citizens’ values and by general expert consensus. Allocation schema for mechanical ventilators, ICU resources, blood components, novel therapeutics, extracorporeal membrane oxygenation, and renal replacement therapies were developed. Creating operational algorithms for each resource posed unique challenges; each resource’s varying nature and underlying data on benefit prevented any single algorithm from being universally applicable. The development of scarce resource allocation processes must be iterative, legally vetted, and tested. We offer our processes to assist other regions that may be faced with the challenge of rationing health-care resources during public health catastrophes.

A resource optimization framework for improving railway-highway grade crossing safety in Canada

This paper presents a new approach to address the problem of allocating federal resources and identifying upgrading projects for improving the safety of at-grade crossings in Canada. The proposed approach is unique in two key aspects. First, a risk-based network screening process is adopted to identify the priority sites for providing a justifiable basis for distributing the total budget at a regional level as well as narrowing the search space in the subject optimization step. Secondly, a mathematical programming approach is applied to formalize the resource allocation process with explicit consideration of the expected benefits – risk reduction and the costs of implementing the projects. This approach is expected to improve the process of identifying the optimal set of upgrading projects within each region, thus maximizing the return on investment. A full-scale case study from the Canadian crossing network is conducted to demonstrate the application of the proposed approach.

Comorbidities and HCV coinfection in the management of HIV+ patients: evidence from the Italian clinical practice

BackgroundSince HIV+ treatment has become more effective, the average age of people living with HIV (PLWHIV) has increased, and consequently the incidence of developing comorbidities, making the clinical and economic management of HIV+ patients more complex. Limited literature exists regarding the management of comorbidities costs. This study is aimed at defining and comparing the total annual costs of comorbidities, in an Italian cohort of HIV and HIV/HCV patients, from the National Healthcare Service perspective. The authors hypothesised that there are higher costs, for patients with multiple comorbidities, and a greater consumption of resources for HIV/HCV co-infected patients versus HIV mono-infected patients.MethodsAn observational retrospective multi-centre health-economics study, enrolling HIV+ and HIV/HCV consecutive patients with at least one comorbidity, was conducted. The consecutive cases, provided by three Italian infectious diseases centres, were related to the year 2016. The enrolled patients were on a stable antiviral therapy for at least six months. Demographic and clinical information was recorded. Costs related to HIV and HCV therapies, other treatments, medical examinations, hospitalizations and outpatient visits were evaluated. Data from mono-infected and co-infected groups of patients were compared, and the statistical analysis was performed by t-tests, chi-square and ANOVA. A sub-analysis excluding HCV therapy costs, was also conducted. The hierarchical sequential linear regression model was used to explore the determinants of costs, considering the investigated comorbidities. All analyses were conducted with a significant level of 0.05.ResultsA total of 676 patients, 82% male, mean age 52, were identified and divided into groups (338 mono-infected HIV+ and 338 co-infected HIV/HCV patients), comparable in terms of age, gender, and demographic characteristics. A trend towards higher annual costs, for patients with multiple comorbidities was observed in HIV mono-infected patients (respectively € 8272.18 for patients without comorbidities and € 12,532.49 for patients with three or more comorbidities, p-value: 0.001). Excluding anti-HCV therapies costs, HIV/HCV co-infected patients generally required more resources, with statistically significant differences related to cardiovascular events (€10,116.58 vs €11,004.28, p-value: 0.001), and neurocognitive impairments events (€7706.43 vs €11,641.29 p- value: < 0.001).ConclusionsThis study provides a differentiated and comprehensive analysis of the healthcare resources needed by HIV and HIV/HCV patients with comorbidities and may contribute to the decision process of resources allocation, in the clinical management of different HIV+ patient populations.

Meta-heuristic algorithms for resource Management in Crisis Based on OWA approach

In crisis management, Threat Evaluation (TE) and Resource Allocation (RA) are two key components. To build an automated system in this area after modelling Threat Evaluation and Resource Allocation processes, solving these models and finding the optimal solution are further important issues. In this paper, Non-dominated Sorting Genetic Algorithm-II (NSGA-II) and Strength Pareto Evolutionary Algorithms (SPEA-II) are employed to solve a multi-objective multi-stage Resource Allocation problem. These Algorithms have been compared using normalized values of the objectives by generational distance, spread, hyper-volume, cardinality and actual computational times. It is found that the non-dominated solutions obtained by SPEA-II are better than NSGA-II both in terms of convergence and diversity but at the expense of computational time. Here, the fuzzy inference systems and the decision tree have been used to conduct threat evaluation process. Finally, Ordered Weighted Averaging (OWA) with maximum Bayesian entropy method for determining the operator weights has been used to pick the final choice among optimal options. We plan to use the proposed method in this paper for crisis management in Iranian Red Crescent organization during fire fighting. Two real studies have been done and results have been presented.

Identifying Key Factors Related to the Resource Allocation in the Health Sector of the Iranian Oil Industry: Application of DEMATEL Method

Background: Resource allocation is one of the major challenges of health systems. Various criteria are used to allocate health resources worldwide. Objectives: The current study aimed to identify and prioritize key factors related to the resource allocation in the health sector of the Iranian Oil Industry using the Decision-Making Trial and Evaluation Laboratory (DEMATEL) method. Methods: This cross-sectional case study was conducted in two main phases during 2017. In the first phase, the literature review and interviews with experts (n = 6) were used to identify initial criteria for resource allocation. Then, considering the views of high and middle managers in the health sector of the Iranian Oil Industry, the final criteria were selected. In the second phase, the DEMATEL technique was used to assess the interactions among the selected criteria. Results: A total of nine criteria were entered into the DEMATEL final questionnaire. Criteria were divided into two main groups of influencing and influenced factors. The high-level documents and general policies of the health system (C1), the burden of diseases (C2), the number of population covered (C4), the infrastructure of the covered regions (C5), and population health needs (C8) were among factors that influenced other factors. Factors such as current budget (C3), the expected benefits of people (C6), the expected benefits of policymakers (C7), and the financial returns of the resource allocation (C9) were among the factors that were influenced by other factors. The number of covered population (C4) and the infrastructure of the regions (C5) were not influenced by other factors but could affect other factors. High-level documents (C1) and the burden of diseases (C2) were identified as independent factors. Conclusions: While allocating resources, policymakers should pay particular attention to influencing factors. The number of population covered in each region and the infrastructure available in each region were identified as key and important criteria in the resource allocation process. It is suggested that these factors be considered while allocating resources to different regions of the country.

Hospital Managers’ Perceptions Regarding Setting Healthcare Priorities in Kuwait

BACKGROUND &amp;amp; OBJECTIVE: In view of the budget limitations resulting from the downturn in the Kuwaiti economy, it is crucial to evaluate the process of priority setting within the health system to identify strengths and weaknesses of this process within both the public and private sectors. Once the weak points are identified, policy makers can work with hospital administration staff to upgrade the process with the aim of utilising health resources more efficiently. The purpose of this study is to give decision makers some insight on the perspective of hospital managers regarding the current process of priority setting, and suggest ways to improve this process. Additionally, this study will provide the opinions of hospital managers in questioning the effect of certain healthcare policies, currently given top priority, on healthcare system efficiency. The views of the hospital managers interviewed indicate their preferences in priority setting and the changes in health spending they believe are required.&#x0D; &#x0D; METHODS: A qualitative study was conducted using semi-structured, face-to-face interviews with 14 managers from public and private hospitals in Kuwait. Content analysis was used to produce major themes and sub-themes from the interview transcripts.&#x0D; &#x0D; RESULTS: While several similarities and differences in the priority-setting process between the public and private sectors were apparent, the main strength in the process that most managers from both sectors mentioned, was that it was simple, systematic, comprehensive and democratic. The several weaknesses of the process include it not being evidence-based due to the lack of accurate and up-to-date data. Also, the discrepancy between the official statements made and the actual practices of health decision makers in the country demonstrate the confusion around the priority-setting process. Most respondents, from both sectors, thought that the availability of a clear and well-communicated national health strategic plan would facilitate the necessary modifications in legislative, structural and administrative strategies to streamline the processes of allocating resources and setting priorities. For example, most respondents believed that the disadvantages of the costly practice of sending patients abroad for treatment and its effect on resource allocation outweighed its advantages. Further, the managers from both sectors had different perceptions regarding the policy of private health insurance for retirees. These two policies, according to some hospital managers, added strain to the health budget and undermined trust in the public-health sector.&#x0D; &#x0D; CONCLUSION: This study examined the perspective of hospital managers regarding the process of healthcare priority setting in Kuwait, and ways to improve it. Priority setting could be improved by having a better understanding of its strengths and weaknesses. The study concludes that health decision makers should remain responsible for accepting and implementing evidence-based, systematic processes of resource allocation. Additionally, continuous monitoring and evaluation of the impact of health policies will be required to improve overall health outcomes.&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;

When the boss is blue: examining the effects of supervisors' negative emotions on subordinates' cognitive work engagement and family undermining

PurposeResearch has largely shown that supervisors' negative emotions lead to subordinates' negative emotions and detrimental work outcomes, but recent studies are showing that supervisor negative emotions may yield both negative and positive subordinate behaviours. Drawing on the work–home resources model, this research sought to unpack the interpersonal, cross-domain effects of supervisor negative emotions on subordinate cognitive work engagement and family undermining through subordinate perceived leader effectiveness and self-efficacy to manage work and life.Design/methodology/approachTo test the relationships, confirmatory factor analysis and structural equation modelling were conducted on time-lagged dyadic data collected from 372 supervisor–subordinate pairs.FindingsResults revealed that supervisor negative emotions led to higher levels of subordinate cognitive work engagement and family undermining.Research limitations/implicationsSupervisor negative emotions had unintended consequences on subordinates' work and family outcomes – they enhanced subordinates' cognitive work engagement (positive work outcome) but also increased subordinates' family undermining (negative family outcome). Future studies could benefit from a diary study with a within-subject design since emotions are known to fluctuate in a day.Practical implicationsThis research provides supervisors with insights about the consequences of their negative emotions on their subordinates, calls upon organisations to provide cognitive regulation training, and encourages subordinates to develop self-efficacy in managing their work and life.Originality/valueThis study is among the first to incorporate self-efficacy to manage work and life as a personal resource and subordinate family undermining as an outcome of supervisor negative emotions, which enhances understanding of the resource allocation and loss processes between supervisors and subordinates.

Sociability Between Coworkers and Social Fit at Work

Social interactions vary across workplaces, in part because workers and managers treat informal social interactions as a facet of workplace cultures, encouraging it in some instances and suppressing it in others. Equally, such interactions are consequential for social capital, and may be a dimension of cultural fit. Thus processes of status attainment and resource allocation may vary across workplaces in concert with their sociability. Using a new measure of time spent with coworkers, constructed using the American Time Use Survey, this paper shows that work explains a great deal more variation in sociability between coworkers than individual characteristics. The extent of shared workplace identities, influenced by occupational competition levels and union membership, and incentives to socialize are two important mechanisms in this process. Moreover, norms and expectations of appropriate behavior in the workplace accompany occupational differences in sociability, and matching these expectations is consequential for workers' earnings.

Biases in Financial Resource Allocation to Subsidiary Projects: The Role of Psychic Distance

This paper investigates biases of senior managers in the financial resource allocation process. In particular, we analyze the role that perceived psychic distance plays in headquarters (HQ) managers’ decisions to fund entrepreneurial initiatives stemming from their subsidiaries. We used an experimental vignette approach with 109 managers from 35 countries. We find that psychic distance to a subsidiary country is negatively related to resource allocation of HQ managers only when proposals were submitted by expatriates. A potential explanation is that expatriates are perceived to lack relevant contextual knowledge for such initiatives to be valuable. This result is particularly striking because the payoff functions of our experimental design were clearly not dependent on these characteristics. We contribute to the literature on psychic distance, biases and resource allocation within multinational corporations (MNCs).

Resource Allocation Scheme for Community-Based Fog Computing Based on Reputation Mechanism

Fog computing needs to seamlessly integrate heterogeneous computing resources widely distributed in edge networks, and then, it can provide unified resources and services for users. However, due to a large number of fog nodes, there are still many security problems in the fog computing process. For example, when fog servers make resource allocation between users' tasks and fog nodes, some fog nodes can falsely claim that they have more resources than their actual ability, so as to get more task processing qualifications. Thus, it will greatly damage the interests of users and affect the quality of service. In this article, we propose a resource allocation scheme for community-based fog computing based on a reputation mechanism. When fog network provides computing services for users, we use a reputation mechanism to enable users to obtain reliable resources in fog computing. In our proposed scheme, a user first submits his/her task request to the community-based fog network, and then, the fog server makes a reliable resource allocation process based on multiple-layer communities and reputation calculation. Based on our experiments, our scheme enables users to obtain reliable resources and improves the service quality of computing resources in fog computing.

DEA‐based centralized resource allocation with network flows

AbstractThis study investigates the centralized resource allocation problem among individual units using network flow theory in a data envelopment analysis (DEA) framework. Existing research on DEA‐based resource allocation is primarily concerned with the amount of allocated resources to individual units, and only a few studies have considered resource flows when resources are allocated. To identify the internal structure of the resource allocation process, network structure is introduced and network flow theory is used to search for the optimal resource allocation scheme. Moreover, resource allocation cost is considered in network flows and a resource allocation gain (RAG) function is formulated to provide a quantitative analysis of the trade‐off between production gains from resource allocation and resource allocation cost in the resource allocation process. In addition, several characteristics of the RAG function are also discussed. Lastly, the proposed method is demonstrated through an expository example with several random data and an application of the centralized resource reallocation to bank systems.

What should be centralized and what should not: that is the question within a school of business context

Learning outcomes The case’s learning objectives to work on can vary according to the topic selected by the teacher. This case has been put forward with a particular interest in corporate strategy issues, specifically, on the joint management of businesses (in this case, academic programs). Therefore, students are expected to be able to understand the managerial dilemma on centralization and decentralization; recognize the peculiarities of a shared services center (SSC); and decide on which services to centralize in an SSC. Case overview/synopsis Centralizing or not centralizing is a frequent managerial dilemma. This is a challenge faced not only by business managers but also by corporate level areas responsible for jointly managing various businesses. Resources and capabilities allocation is an essential process for strategy execution, specifically in corporate strategy that must answer the question: How to jointly manage businesses? Sharing services is a collaborative strategy which aims to increase efficiency by centralizing some processes related to this joint business management. Mario, Dean of the Escuela de Administración in Medellín, Colombia, intends to optimize the school resource allocation processes so that there is more equitable support between the different academic programs. For this, he has thought of creating an SSC as it is a practice that he has seen in prominent companies in the city. His idea is to start operating the SSC in early 2018; however, the particular character of a management school leads him to ask himself: What to centralize and what not to centralize? Complexity academic level This case of decision (Ellet, 2007; Sánchez et al., 2013) can be used to promote student learning of strategy courses both at advanced undergraduate levels and in graduate programs. Likewise, it can be used in workshops with executives and administrative personnel of companies that face the centralize–decentralize dilemma. These types of topics are the subject of study by both corporate strategy theorists who address the question of how to jointly manage business (Menz et al., 2015; Michael Porter, 1987) and consultants (Deloitte, 2012). It is desirable, although not mandatory, that students have some knowledge or experience in strategic issues and challenges associated with the administration of companies made up of various businesses (multi-business firms). Supplementary materials Teaching Notes are available for educators only. Subject code CSS 11: Strategy.

Participatory Budgeting in the Philippines

Participatory budgeting has been adopted and adapted by governments around the world. Existing literature points to a variety of desired outcomes from these efforts, but does not clearly distinguish the impacts on individuals, groups, and society. This study uses the case of the Philippines to explore the differences in impacts of participatory budgeting within and across the three levels. Reforms in the Philippines were similar to efforts in other countries, but there were adaptations, including a national mandate for the decentralization of participatory budgeting to local governments and the required representation of civil society organizations in local resource allocation processes. Some gains in individual education and efficacy, representation of marginalized groups and social justice, and government accountability were seen in the Philippines, but they seem to be idiosyncratic to the local context. Civil society and democratic legitimacy advances, though, were weaker, at least partly due to challenges in involving third-party intermediaries in the process, and continued issues with elitism and corruption. Like other participatory budgeting cases, the outcomes have not been uniform, and transitions in national leadership hinder institutionalization.

Allocation algorithm of CPS communication resources based on cooperative game

In order to improve the communication rate of the cyber–physical fusion system, and at the same time guarantee the quality of system demand of each user, a CPS (Cyber–Physical Systems) communication resource allocation algorithm based on cooperative game was first proposed. The resource allocation process of the orthogonal frequency division multiple access network downlink in CPS is modeled as a cooperative game among multiple users, and the Pareto optimality among users is achieved by solving the Nash bargaining solution. Secondly, this paper studies the cooperative task assignment of communication resources for actuators in CPS execution network, and proposes a feasible task assignment method of communication resources based on K–M algorithm. Simulation experiments show that the task allocation result obtained by this method is better than that of auction method, and the algorithm running time can also meet the limit of actual demand. Finally, in consideration of the control center’s need for fine control of the actuator, this paper studies the wireless resource allocation problem between a control center and the actuator, and maximizes the control effect of the actuator as the daily standard, and proposes a dynamic Joint allocation scheme of subchannels and power. Simulation results show that the proposed scheme can maintain a high level of control effect even when the transmission power of the control center is small, which effectively saves the energy consumption of the control center.