Optimal Allocation Of Human Resources Research Articles

Research on Human Resource Allocation Algorithm for Application Integration Feature Selection in the Internet of Things Environment

Abstract In the context of the Internet of Things, the existing human resource optimization allocation methods have problems such as time-consuming resource allocation, improper allocation, improper matching between tasks and resources, and unsatisfactory human resources. This paper proposes a new human resource allocation method based on the multi-objective method, that is, the use of comprehensive feature selection for resource allocation. The method first extracts human resource features to establish a database, then completes feature selection based on the comprehensive feature selection method, establishes the human resource allocation model, and allocates resources according to various factors and resource characteristics. Finally, the genetic algorithm is used to solve the human resource allocation model to achieve the optimal allocation of human resources. The experimental results show that the proposed method takes a shorter time to allocate human resources and a shorter time to execute tasks after the allocation is completed, which verifies the high scheduling efficiency and effectiveness of the proposed method.

Facility staffing associated with potentially avoidable hospitalizations in nursing home residents in Japan: a retrospective cohort study

BackgroundWide variations in facility staffing may lead to differences in care, and consequently, adverse outcomes such as hospitalizations. However, few studies focused on types of occupations. Therefore, we aimed to examine the association between a wide variety of facility staffing and potentially avoidable hospitalizations of nursing home residents in Japan.MethodsIn this retrospective cohort study using long-term care and medical insurance claims data in Ibaraki Prefecture from April 2018 to March 2019, we identified individuals aged 65 years and above who were newly admitted to nursing homes. In addition, facility characteristic data were obtained from the long-term care insurance service disclosure system. Subsequently, we conducted a multivariable Cox regression analysis and evaluated the association between facility staffing and potentially avoidable hospitalizations.ResultsA total of 2909 residents from 235 nursing homes were included. The cumulative incidence of potentially avoidable hospitalizations at 180 days was 14.2% (95% confidence interval [CI] 12.7–15.8). Facilities with full-time physicians (adjusted hazard ratio [HR]: 0.59, 95% CI: 0.37–0.94) and a higher number of dietitians (HR: 0.72, 95% CI: 0.54–0.97) were significantly associated with a lower likelihood of potentially avoidable hospitalizations. In contrast, having nurses or trained caregivers during the night shift (HR: 1.72, 95% CI: 1.25–2.36) and a higher number of care managers (HR: 1.37, 95% CI: 1.03–1.83) were significantly associated with a high probability of potentially avoidable hospitalizations.ConclusionsWe revealed that variations in facility staffing were associated with potentially avoidable hospitalizations. The results suggest that optimal allocation of human resources, such as dietitians and physicians, may be essential to reduce potentially avoidable hospitalizations. To provide appropriate care to nursing home residents, it is necessary to establish a system to effectively allocate limited resources. Further research is warranted on the causal relationship between staff allocation and unnecessary hospitalizations, considering the confounding factors.

Informatization Management and Optimal Allocation of Human Resources in Engineering Projects

Based on the engineering projects in progress, this paper aims to explore the improvement of human resource informatization management in engineering projects from the perspective of personnel allocation benchmark, automatic recommendation of professional title evaluation and visual management of cadre gap. In terms of optimal allocation of human resources, it focuses on optimizing the allocation of human resources in the engineering projects from the aspects of recruitment cycle, channel management and inter-project personnel recommendation, which provides a new development idea for the human resources management of engineering projects in the face of the digital transformation of enterprises today.

Performance optimization of pillow sheet set sewing assembly line by SAM analysis and lean manufacturing techniques of method study & work measurement

This research was conducted to enhance the productivity of the targeted sewing line at the ABC textile company. The existing SAMs, the capacity of the sewing line for various operations, and several required machines were collected. Moreover, the obtained figures were observed and analyzed by using time study and motion study, and certain improvements were made at the sewing line. Results indicated that SAMs for operations A and B were minimized by -13.64% and -14.54% respectively; whereas, SAM for operation C was increased by 16.67%. Machine requirement for operation C was increased by 100%; moreover, the capacity for operations A, B, and C was increased by 12%, 12.69%, and 40% respectively. When it is to production activities, the little improvements play a significant role in boosting the productivity of the production system. Optimal allocation of human resources, machines, and time are the benefits of line balancing. This can be made possible with the application of the line-balancing framework. With every passing day, the nature and type of article vary at the sewing line thus it is highly needed for the company to get the model developed for an automated line balancing application. Moreover, this work can be extended by the development of a line-balancing framework considering the nature of production.

Research on the Mathematical Model for Optimal Allocation of Human Resources in the Operation and Maintenance Units of a Heavy Haul Railway

According to the existing personnel structure, quantity, development strategy, and market demand of the Shuohuang Railway Company’s operation and maintenance project, the demand quantity of various employees of the company for the past three years is predicted, and a human resource optimization model based on existing human resources and future plans is established. Then, the optimal solutions of the two mathematical models were calculated and analyzed using LINGO software. Finally, combined with the actual situation, the optimal allocation of human resources for the operation and maintenance project of KY company was obtained. The following conclusions are obtained. (1) For the optimal allocation model of existing human resources, the maximum net profit of the optimal staffing model is CNY 3258000. (2) The human resources allocation cost of the minimum dismissal model is CNY 81000. (3) The human resources allocation cost of the lowest cost model is CNY 15500. The research results can effectively guide the human resource management of the operation and maintenance project of the Shuohuang Railway Company, and have important theoretical and practical significance for further analysis of human resources model and its optimal allocation method.

Correspondence Model of Human Resource Management and Marketing Based on Genetic Algorithm

In order to realize the optimal allocation of human resources and avoid the waste or relative shortage of human resources, human resources and marketing based on the genetic algorithm are combined together and a combined evaluation management model is established in this study. By constructing a weight vector to represent the evaluation performance of different evaluation models for talent evaluation, the combination problem of multiple evaluation models is transformed into an optimization problem of weights. Based on the evaluation accuracy, the fitness function is designed, the weight vector is optimized by the genetic algorithm, and the individual selection strategy is designed to avoid falling into local optimization. The validity of the model and algorithm is verified by a numerical example, and the calculation results show that the proposed method can gradually improve the average working ability of employed employees by reasonably controlling the number of employment at different periods and the number of dismissals, and the average working ability of employees can be improved by 41%, thus realizing the optimization of human resources for the project.

Allocation Method of Enterprise High-Quality Human Resources Based on Intelligent Big Data

At present, the variation coefficient is used to calculate the difference between personnel and individual posts, which leads to the poor ability of allocating enterprise human resources. Therefore, a high-quality enterprise human resource allocation method based on intelligent big data is proposed. According to the four principles, the process of model building is designed, the hypothesis of model building is made, and the model of optimal allocation of human resources is constructed. From the personnel and post quantity, personnel and post structure, personnel and post quality, system, and other four aspects of optimal allocation, design the model running process, network personnel and posts, and use network indicators to match personnel and posts. The adjustment layer is introduced into the basic CNN model structure, and the input layer of intelligent big data is used to normalize the score of current high-quality human resources of enterprises. After the local characteristic processing is implemented on the human resource scoring matrix, the human resource allocation results are output to realize the allocation of high-quality human resources of enterprises. The experimental results show that the evaluation effect of the method is good, the evaluation time is short, the work efficiency is high, the credibility of human resource structure allocation is good, and the human resource allocation method has a good human resource structure allocation ability.

Enterprise Human Resource Allocation Optimization Model Based on Improved Particle Swarm Optimization Algorithm

With the development of the market economy, the competition for talents among enterprises has attracted more and more attention. Therefore, in recent years, enterprises have paid more and more attention to the optimal allocation of human resources. Aiming at the problem of human resources allocation in the process of enterprise management, this research establishes a corresponding mathematical model and solves the optimal allocation model of human resources based on particle swarm optimization algorithm. The calculation amount of the model is obviously reduced in the application process, the optimal solution is more ideal, and good results are achieved. However, the genetic algorithm itself has certain limitations, and the selection of initial chromosomes and the design of genetic operators put forward higher requirements. Starting from operability, based on system analysis and quantitative evaluation method, this paper establishes a model of human resources optimal allocation, provides a quantitative management method for optimal allocation of human resources, and designs an improved particle swarm optimization algorithm to solve this problem. The numerical simulation results show the effectiveness of the algorithm.

Sustainability and Optimal Allocation of Human Resource of Agricultural Practices in Sistan and Baluchestan Province Based on Network DEA

The agricultural sector ensures food security in every country.Optimal agricultural practices presuppose the optimal allocationof resources, including water, soil, etc., by official authorities in everycountry because excessive use of natural resources would have harmfulconsequences for posterity despite meeting ad hoc needs. Therefore,sustainable agricultural practices in different regions should be basedon environmental, social, and economic criteria in the decision-makingprocess for the future. This study investigated the agricultural practicesin two stages: environmental stage (planting and maintaining)and economic stage (harvesting), which use shared resources. A networkDEA model was proposed for developing sustainable agriculturalpractices based on the proposed process. The development of sustainableagricultural practices in different regions presupposes the optimal allocation of water and human resources, which is realized by the improvementof irrigation methods and the quality of life of farmers. Innetwork DEA models, weight restrictions are used to determine sustainabledevelopment. The proposed model was analyzed with and withoutweight restrictions to determine the sustainable development of agriculturein Sistan and Baluchestan Province, Iran, between 2013 and 2017.On the other hand, given the important role human resources play inthe development of sustainable agricultural practices, some models weresuggested for determining the maximum required human resources foreach stage according to the obtained performance levels.

“Internet + Artificial Intelligence” Human Resource Information Management System Construction Innovation and Research

Human resources are the cornerstone of operational operation. Good management of human resource information can enable businesses to operate effectively. However, for the time being, most enterprises still use traditional methods of allocating human resources, which are difficult to meet the development needs of enterprises. In order to find the optimal allocation of human resources in an enterprise, this article is based on “Internet + artificial intelligence,” using methods such as case analysis and literature analysis to collect data from databases such as CNKI, Wanfang Database, and SSCI, and uses fog computing to build a model for the optimal allocation of human resources which is proposed, and a large number of relevant literature studies are read and analyzed through the literature survey method. According to the research needs, through the research and summary of the content of the literature, the research structure found that there are many problems in the current human resource information management system. After the optimization of models and algorithms, the allocation of human resources has been greatly improved. The matching rate of personnel and job positions has increased by more than 50%. The operation efficiency index of the enterprise is above 0.8, an increase of about 30%. This shows that “Internet + artificial intelligence” can effectively optimize the enterprise human resource information management system, promote the greater use of its human resource value, bring higher economic returns to the enterprise, and provide assistance for the long-term stable and healthy development of the enterprise.

A model for optimal allocation of human resources based on the operational performance of organisational units by multi-agent systems

Optimal allocation of human resources is studied in this research. To solve the problem, a model of negotiation between intelligent agents is used in this study. Organisational units are considered as agents that seek for their benefits and use negotiation for human resources and job distribution. We firstly introduce operational performance level to find out how units can guarantee their performance. As a result, in this research, organisational decision making is managed in two levels by agents. In medium level, agents negotiate each other using optimal function to divide human resources optimally. Therefore, the final agreement will be distributed among the organisation using the special function developed for this reason. Results have shown that organisational units' operational performance is a good criterion for human resources distribution in organisation.

A model for optimal allocation of human resources based on the operational performance of organisational units by multi-agent systems

Optimal allocation of human resources is studied in this research. To solve the problem, a model of negotiation between intelligent agents is used in this study. Organisational units are considered as agents that seek for their benefits and use negotiation for human resources and job distribution. We firstly introduce operational performance level to find out how units can guarantee their performance. As a result, in this research, organisational decision making is managed in two levels by agents. In medium level, agents negotiate each other using optimal function to divide human resources optimally. Therefore, the final agreement will be distributed among the organisation using the special function developed for this reason. Results have shown that organisational units' operational performance is a good criterion for human resources distribution in organisation.

An integrated machine scheduling and personnel allocation problem for large-scale industrial facilities using a rolling horizon framework

In this study we present an optimization problem where machine scheduling and personnel allocation decisions are solved simultaneously. The machine scheduling consists of solving a variant of the job shop problem where jobs are allocated in batches and multitasking is allowed. On the other hand, the personnel allocation problem searches for the optimal allocation of human resources to support the facility operation. Although these problems have been extensively studied independently in the literature, the integrated problem has very limited studies, in particular for large-scale industrial environments. We introduce a mathematical formulation for this problem and propose a solution method to evaluate optimal solutions more efficiently. We also implement a rolling horizon framework to test our approach using real-world based instances extracted from an analytical service facility. The results show that, overall improvements of up to 11.6% are achieved compared to the case where no personnel allocation decisions are considered within the scheduling problem.

Optimal allocation of human resources based on operational performance of organizational units using fuzzy game theory

The allocation of human resources is considered as one of daily challenges of many organizations to achieve optimal efficiency. After investigating this challenge, in this research, a multi-agent s...

Optimizing Human Resource Allocation in Organizations During Crisis Conditions: a P-graph Approach

The onset of climate change is expected to bring about more severe weather patterns which may lead to floods, drought, and even the outbreak of new types of diseases. These can potentially disrupt the operations of industries and firms as infrastructure can be damaged and the availability of resources and workforce are compromised. It is thus important to develop models which will assist in the efficient management of resources during times of crisis. Process systems engineering techniques have previously been used for the design and optimization of complex systems during crisis conditions. This work presents the development of a P-graph model for the optimal allocation of human resources within a firm when the available workforce has been limited due to a climate change-induced crisis. The model identifies an optimal strategy for maximizing firm productivity by prioritizing highly critical areas.

Optimal allocation of human resources in the emergency ambulance service

Optimal allocation of human resources in the emergency ambulance service

Construction and Analysis of the Decision Model based on the Transfer of Human Resources

The transfer of human resources refers to the transfer of human resources across different regions, industries and organizations depending on the development trends in the respective areas, economic environment and personal development needs. It is a process where the revenue of human resources improves continuously, and regional economy, industries and organizations are growing. Reasonable transfers across regions, industries and organizations can further realize the potential of individuals and enhance their advantageous position in the job market. Moreover, the transfers can optimize human resource allocation and the overall regional industrial development, improving the utilization of human resources. According to the law of diminishing returns, when there is perfect competition across regions, industries and organizations, the marginal utility of the side that has human resources shortage is higher than the side that has surplus. The human resources will flow to the side with shortage till the marginal revenue of the two sides reaches equilibrium. This is the ideal condition for human resources transfer. This paper is aimed to build models for individual human resource decisionmaking, organizational decision-making and dynamic balance respectively, in order to facilitate the equilibrium transfer of human resources across different regions, industries and organizations, and finally to achieve the optimal allocation of human resources.

Preliminary Study about Optimal Allocation of Human Resources Management

In today's world, the competition between enterprises in the final analysis is talent competition and giving full play to the role of talents of enterprise cannot leave the optimal allocation of human resources. Along with the increasing open of global economy, our state-owned enterprises face the more and more difficult challenge, but also have many opportunities, which will encourage enterprises to renew ideas, adjust human resource structure, strengthen the cultivation of talents, learn and introduce advanced hr optimization technology and method. In Nanyang mobile company, for example, on the basis of expounding the connotation and principle of human resources optimization allocation, the paper summarizes and analyzes the human resource configuration optimization problems and also puts forward some proposals for resolving these problems using human resource configuration optimization theory. By means of human resource configuration optimization, it can realize company efficient, orderly and long-term development, and provides some suggestions about hr optimization for other companies.

Treatment of Hawks and Doves

The paper investigates the optimal allocation of human resources both theoretically and empirically. The theoretical part shows that some wage compression is desirable for the following two cases; (1) hawks (i.e., uncooperative and aggressive workers) work together, or are in the common work-place, and (2) hawks and doves (i.e., cooperative and less aggressive workers) work together, and seek promotion in the competitive world. The empirical part presents the result for Japan. We find that large Japanese firms had wage compression for younger generations in order to minimize the degree of adverse effort caused by the behavior of hawks. At the same, we try to find, “Who is likely to be hawkish?”