Operations Management Problems Research Articles

Управление результативностью микрофинансовых организаций предпринимательского финансирования с использованием алгоритмов машинного обучения

Article discusses theoretical problems of performance management of microfinance organizations as a hybrid form of entrepreneurship with dual objectives. The paper presents scoring models of decision-making on granting loans by public microfinance organizations of entrepreneurial finance based on forecasting the growth of borrowing companies. The models are built on the basis of data from 252 SME companies that received financial support from state microfinance organizations in Primorsky and Khabarovsk Krai for the period 2019-2022. The results demonstrate the high accuracy of the obtained models and their performance is confirmed by out-of-sample forecasting results. The theoretical result of the study is the development of an approach that allows integrating the principles of strategic management with the concept of value creation of public microfinance organizations. The practical significance stems from the development of a flexible decision-making algorithm that allows the management of microfinance organizations to adjust the criteria for selecting borrowers in accordance with the organizations’ strategic objectives. The algorithm assumes an ensemble structure of decision-making, where the manager of a microfinance organization receives an automated decision, but remains responsible for its result.

Research on the Optimization Strategy of Performance Management Framework of Chinese Basic Education Schools from the Perspective of Organizational Structure

The school is essentially an organization so the rationality and scientificity of its organizational structure design are of great importance to improving the effectiveness of school governance. Based on the perspective of organizational structure, this paper analyzes the current problems of performance management in basic education in China and tries to put forward some optimization strategies for the school performance management framework, to promote the long-term development of China’s basic education.

Dynamic collaborative truck-drone delivery with en-route synchronization and random requests

Coordinated truck and drone delivery is gaining popularity in logistics as it can greatly reduce operation costs. However, existing studies on related operations management problems typically ignore the following important features: (i) the random appearance of requests, which require operators to dynamically respond to the requests; and (ii) the decisions of optimal launch and retrieval locations for trucks and drones instead of fixed to customer locations, which can significantly impact the overall time costs. To tackle these challenges, this study investigates the dynamic collaborative truck-drone routing problem with randomly arriving requests and synchronization on routes. We model the problem as a Markov Decision Process (MDP) and solve the MDP via a reinforcement learning (RL) approach. The proposed RL approach determines: (i) whether each request should be serviced upon arrival, (ii) which truck or drone should be assigned for the request, and (iii) the optimal en-route take-off and landing positions for paired trucks and drones. We further employ a framework of decentralized learning and centralized dispatching in RL to increase performance. Numerical experiments are conducted to assess the proposed solution approach on instances generated based on both the Solomon dataset and real-world operational data of a logistics operator in Singapore over several benchmark algorithms under various battery endurance levels of drones and distinct transportation scenarios including node-based dynamic collaborative truck-drone routing problem, dynamic non-collaborative truck and drone routing problem, and dynamic vehicle routing problem. The results show that our RL solution outperforms the benchmark algorithm in total profit by an average of 28.03 %, and our en-route takeoff and landing scenario outperforms the benchmark scenarios in total profit by an average of 8.43 % in multi-day instances. Additionally, compared to the traditional node-based landing scenario, employing our en-route takeoff and landing strategy can save 0.9 h/(drone*day) of waiting time on average.

Learning From User-Specified Optimizer Hints in Database Systems

Abstract Recently, numerous machine learning (ML) techniques have been applied to address database performance management problems, including cardinality estimation, cost modeling, optimal join order prediction, hint generation, etc. In this paper, we focus on query optimizer hints employed by users in their queries in order to mask some Query Optimizer deficiencies. We treat the query optimizer hints, bound to previous queries, as significant additional query metadata and learn to automatically predict which new queries will pose similar performance challenges and should therefore also be supported by query optimizer hints. To validate our approach, we have performed a number of experiments using real-life SQL workloads and we achieved promising results.

Strengthening Higher Education performance Management

This study aims to examine the institutional and operational dimensions of performance management of the Government Agency Performance Accountability System (SAKIP) of Higher Education. Empirically, the strengthening of both dimensions in higher education performance management includes, 1) Institutional guarantees stably through commitment, legitimacy, and digital leadership. 2) Operational systems through planning, measurement, and internal reporting and evaluation. To achieve the objectives of this research qualitative descriptive method was used. This research method is used to reveal the problems of higher education performance management. This research was conducted at Gorontalo State University (UNG). The informants of this research include elements of leadership, management team, lecturers, and education personnel who are directly involved and influenced by decision-making. Data collection was carried out by interview, observation, and documentation which were then analyzed using the Miles and Huberman data analysis technique. The research findings show that performance management at UNG can be seen fundamentally and in a more macro perspective by, 1) The legality of providing internal policies as guidelines in carrying out university performance in a stable manner. 2) Information technology support through an integrated system of information systems in supporting the operational mechanism of higher education performance data management. Keywords: technology support, data integration, electronic system, internal policy, legality

КЛЮЧЕВЫЕ СТРАТЕГИЧЕСКИЕ НАПРАВЛЕНИЯ РЕШЕНИЯ ПРОБЛЕМ УПРАВЛЕНИЯ ПРОИЗВОДИТЕЛЬНОСТЬЮ В СОВРЕМЕННОЙ ОРГАНИЗАЦИИ

The article examines the key problems of performance management within the framework of strategic management of an organization. The main factors shaping the occurrence of problems are analyzed and ways to solve performance management problems are proposed. Combinations of strategies have been formed to increase the efficiency of personnel.

정수 선형 분수 계획법 문제에 대한 파라메트릭 접근법

In this paper, we focus on the integer linear fractional optimization problem, a special case of fractional programming where all functions in the objective function and constraints are linear and all variables are bounded and discrete. To derive the optimal solution, the parametric algorithms are considered, and the efficiency of the algorithms is investigated computationally. Unlike traditional parametric algorithms such as Newton's method, which create a unidirectional sequence approaching the optimal function value, our proposed algorithm generates both upper and lower bounds converging to this value. To demonstrate its effectiveness across various production and operations management problems, the suggested algorithms are used to solve the fractional knapsack problem by comparison to other algorithms (e.g., Newton’s method) under the randomized experimental conditions. The relative practical performance measured by the number of function calls demonstrates that the proposed algorithms are fast and robust for solving the linear fractional programs with discrete variables. Leveraging this algorithm holds the potential to overcome situations in traditional production and operations problems where non-fractional objective functions were previously unconsidered, thereby expecting to derive new outcomes and significance.

Методы поддержки принятия решений в оперативном управлении при чрезвычайных ситуациях: обзор исследований

The article examines the problem of operational management in emergencies. At the content level, an analysis of strategic, tactical and operational management in emergency situations was carried out, and their intended purpose was determined. The content of operational management decisions at different stages of emergency situations has been studied. Limitations that directly affect operational management in emergencies have been identified. 
 A systematic analysis of scientific research is carried out and examples are given in the context of work related to operational management in emergencies regarding the stages of emergency development. Research highlights include articles in the fields of mathematical modeling, simulation modeling, game theory and decision making, artificial intelligence and knowledge management. The main promising directions for further research have been identified.

An Adaptive Robust Optimization Model for Microgrids Operation Using Convexified AC Power Flow Equations

Considering the increasing penetration of renewable energy sources (RESs) into power grids, adopting efficient energy management strategies is vital to mitigate the uncertainty issues resulting from the intermittent nature of their output power. This paper aims to resolve the energy management problem by presenting an adaptive robust optimization (ARO) model in which uncertainties associated with solar and wind powers, consumer demand, and electricity prices are considered. The proposed model comprises three stages, one master and two subproblems, using both linearized and convexified power flow equations. Meanwhile, a new optimization-based bound tightening (OBBT) method is also presented to strengthen the relaxation. The proposed solution method solves the microgrid (MG) operation management problem with high accuracy due to considering the convexification method in a reasonable computational time and reducing operational costs compared to conventional models. The numerical results indicate the benefits of the proposed ARO and solution approach over traditional methods.

Privacy-Preserving Operation Management of Battery Swapping and Charging System With Dual-Based Benders Decomposition

The battery swapping and charging system (BSCS) is an emerging and promising infrastructure to provide the energy refueling service for EVs. However, each operator (i.e., battery swapping module (BSM) operator and battery charging module (BCM) operator) in BSCS has privacy-preserving requirement and individual interest, which brings challenge to the operation management of BSCS. To this end, this paper investigates the privacy-preserving operation management problem (OMP) of BSCS from a social perspective, in which a comprehensive battery-swapping-charging process is modeled. Specifically, we first model the OMP as a constrained mixed-integer programming (MIP), where the evolutionary of the dynamic battery inventory and the SoC of charging batteries are considered simultaneously. Due to the privacy-preserving requirements of different operators and the strong coupling between continuous and binary decision variables, a novel dual-based Benders decomposition (DBD) algorithm is then developed, which has the following two merits: 1) Each BCM and BSM operator can independently solve its own charging and swapping scheduling problem, thus preserving the privacy of individual operator; 2) The combination of dual decomposition and Benders decomposition techniques facilitates a parallel implementation, thus improving the scheduling efficiency and saving the computational time. Finally, simulation results are provided to validate the effectiveness and scalability of the proposed algorithm.

Research on Optimization Strategies of Employee Performance Management in K Engineering Company

This article takes employees of K Engineering Company in Guizhou Province as the research object, and uses literature research, interview, and questioning methods The questionnaire survey method and empirical research method are used to analyze the current implementation status of performance management in K Engineering Company, identify the main problems in its performance management, and finally propose specific and feasible optimization plans for the identified problems. This article adopts data from a questionnaire survey conducted on employees of K Engineering Company, and through empirical analysis of the company's strategic policies and development goals, it is found that there are several problems in the performance evaluation of K Engineering Company employees, such as unreasonable setting of evaluation indicators during the performance goal setting stage, and inconsistency between performance management and job positions; In the performance monitoring and coaching stage, there are problems with a single performance monitoring method and a mere formality in performance coaching; In the execution stage of performance appraisal, there are problems such as ineffective performance appraisal methods, unfair company performance appraisal, and low participation of company performance appraisal employees; In the feedback stage of performance application, there are issues such as the lack of established performance communication and feedback channels, the insignificant incentive effect of employee performance management, and low satisfaction with the application of employee performance evaluation results. Analyze the reasons for the problems in employee performance management of K Engineering Company, propose an optimization plan for performance evaluation of relevant personnel, and optimize performance evaluation indicators, content, cycle, feedback and application of performance results, I hope that the research in this article can provide assistance to K Engineering Company in terms of performance management system, and can provide guidance for K Engineering Company Contribute to high-quality development.

Using the integration of human resource management strategies at district level to improve workforce performance: analysis of workplan designs in three African countries

BackgroundThere is a worldwide shortage of health workers against WHO recommended staffing levels to achieve Universal Health Coverage. To improve the performance of the existing health workforce a set of integrated human resources (HR) strategies are needed to address the root causes of these shortages. The PERFORM2Scale project uses an action research approach to support district level management teams to develop appropriate workplans to address service delivery and workforce-related problems using a set of integrated human resources strategies. This paper provides evidence of the feasibility of supporting managers at district level to design appropriate integrated workplans to address these problems.MethodsThe study used content analysis of documents including problem trees and 43 workplans developed by 28 district health management teams (DHMT) across three countries between 2018 and 2021 to identify how appropriate basic planning principles and the use of integrated human resource and health systems strategies were used in the design of the workplans developed. Four categories of HR strategies were used for the analysis (availability, direction, competencies, rewards and sanctions) and the relationship between HR and wider health systems strategies was also examined.ResultsAbout half (49%) of the DHMTs selected service-delivery problems while others selected workforce performance (46%) or general management (5%) problems, yet all workplans addressed health workforce-related causes through integrated workplans. Most DHMTs used a combination of strategies for improving direction and competencies. The use of strategies to improve availability and the use of rewards and sanctions was more common amongst DHMTs in Ghana; this may be related to availability of decision-space in these areas. Other planning considerations such as link between problem and strategy, inclusion of gender and use of indicators were evident in the design of the workplans.ConclusionsThe study has demonstrated that, with appropriate support using an action research approach, DHMTs are able to design workplans which include integrated HR strategies. This process will help districts to address workforce and other service delivery problems as well as improving ‘health workforce literacy' of DHMT members which will benefit the country more broadly if and when any of the team members is promoted.

MATHEMATICAL MODELLING OF WATER REGULATION PROCESSES ON DUAL-ACTION DRAINAGE SYSTEMS

The solution of the problem of increasing water regulation areas in the Polissia zone of Ukraine requires investigation and development of new, more effective methods for determining structural parameters of drainage systems when developing projects for their reconstruction in accordance with the requirements aimed at ensuring water regulation during systems’ operation. The paper considers the problem of improving the efficiency of water regulation on dual-action drainage systems by using mathematical modelling tools to determine the structural parameters of the systems and the parameters of their operational management. The proposed means are based on the use of Richards equation stated in terms of water head. As a tool for scenario modelling, an initial-boundary value problem of modelling moisture transfer on dual-action systems is formulated and a finite-difference scheme for obtaining its numerical solution is given. We consider the problem of determining the depth of drains installation and the distance between them at which the system provides not only the drainage of soil’s surface layer, but also the maintenance of its moisture supply level in a given range with a minimum need for irrigation during the growing season. The algorithm for solving such a problem is presented. It is based on the construction of a set of admissible values of system’s parameters using, in particular, the bisection method, followed by the minimization of an objective function on this set. Under the conditions when the implementation of underground water supply technology is economically impractical, the possibility of supplementing the drainage system with an irrigation system is considered. In this case, the cost of building a drainage system and an additional irrigation system is a criterion for the optimality of system’s parameters. Additionally, we consider the problem of operational management of water regulation, i.e., the determination, given the initial distribution of moisture, of the optimal control influences necessary to ensure an acceptable level of moisture availability during a given period of time. This minimization problem is proposed to be solved by a genetic algorithm. The results of modelling the operation of a dual-action system and the optimization of its parameters under the conditions of drained peat soils of the Panfyly Research Station (Ukraine, Kyiv region) are presented.

Modeling repair demand in existence of a nonstationary installed base

Life cycles of products consist of 3 phases, namely growth, maturity, and decline phases. Modeling repair demand is particularly difficult in the growth and decline stages due to nonstationarity. In this study, we suggest respective stochastic models that capture the dynamics of repair demand in these two phases. We apply our theory to two different operations management problems. First, using the moments of spare parts demand, we suggest an algorithm that selects a parametric distribution from the hypergeometric family (Ord, 1967) for each period in time. We utilize the algorithm in a single echelon inventory control problem. Second, we focus on investment decisions of Original Equipment Manufacturers (OEMs) to extend economic lifetimes of products with technology upgrades. Our results indicate that the second moment is sufficient for growing customer bases, whereas using the third moment doubles the approximation quality of theoretical distributions for a declining customer base. From a cost minimization perspective, using higher moments of demand leads to savings up to 13.6% compared to the single-moment approach. Also, we characterize the optimal investment policy for lifetime extension decisions from risk-neutral and risk-averse perspectives. We find that there exists a critical level of investment cost and installed base size for profitability of lifetime extension for OEMs. From a managerial point of view, we find that a risk-neutral decision maker finds the lifetime extension problem profitable. In contrast, even a slight risk aversion can make the lifetime extension decision economically undesirable.

Research and implementation of non-linear management and monitoring system for classified information network

Abstract In order to better realize the secret-related information monitoring system, an algorithm based on a nonlinear network is proposed and is combined with the traditional algorithm. This article mainly analyzes the theory of nonlinear networks, designs and trains new network parameters according to their own needs, and combines the nonlinear network as a feature extractor with the existing intrusion detection and wandering detection algorithms, which greatly improves the recognition ability of traditional algorithms. The main feature of a nonlinear network is that it can extract the positional features of objects from the network while also extracting object features, that is, positioning and classification are realized in the same network. As a feature extractor, this network can not only have a higher recognition rate than background difference, hog, and other algorithms but also have a greater ability to extract position information than other convolutional neural networks. The successful application of nonlinear production network systems in TV stations at all levels has greatly improved the editing and production capability and efficiency of TV programs. How to ensure the safe, reliable, stable, orderly, and efficient operation of nonlinear production network systems requires vendors and TVS Taiwan technical staff to jointly conduct in-depth research and summarize their findings. In this article, from the perspective of TV users, information components in nonlinear production network systems are analyzed, including class, title management mode, storage space management, material management, security management, and workflow management in nonlinear systems. Make some analysis, discussion, and summaries of network system and operation management problems. The experimental results show that the nonlinear algorithm in this article has a significant advantage over the original tracking algorithm; that is, most tracking algorithms do not have the ability of category recognition during the initial tracking process, which means that these tracking algorithms cannot accurately know what they are tracking. Because the nonlinear network has the ability to output categories, whether it is initial tracking or tracking loss recovery, nonlinearity has fundamentally better advantages than other tracking algorithms. Therefore, it can be predicted that there is a strong recognition ability in the later monitoring and wandering detection. It has been proved that the nonlinear algorithm can be effectively applied to the secret information monitoring system.

Research on Teachers’ Performance Management Problems in Yulin Vocational and Technical College and Solutions

Research on Teachers’ Performance Management Problems in Yulin Vocational and Technical College and Solutions

Research on the Performance Management Problems of Gushi Rural Commercial Bank

The continued development of China's market economy has resulted in the Rural Commercial Banks expanding their business scale, however, traditional individual performance measurement models have had difficulty adjusting to the bank's deepening development needs. It is important that Rural Commercial Banks concentrate on accurate positioning and development goals and continuously optimize the current performance management system to mobilize the enthusiasm of personnel and improve work efficiency. This paper mainly explores the performance management problems of Gushi Rural Commercial Bank and suggests ways to formulate performance management plans tailored to its characteristics with a focus on improving performance assessment feedback and communication systems, clarifying assessment performance, implementing assessment results more effectively, and strengthening the application of assessment results.

Research on operation management problems in the takeaway express delivery industry: A case study on the operation and management of "Meituan" takeaway

In recent years, people's standard of living has been rising and the pace of life has become increasingly fast, with higher demands on dietary conditions as well as the need for more efficient and convenient meal times to save time for work and other activities. As a result, there is a clear prospect of a booming takeaway industry, which is of wide interest to all sectors of society. This study will use literature search and case studies as the main research methods, focusing on the operation and management of Meituan's takeaway, and analyses its business model, business pain points and dilemmas, and make suggestions for improving and refining the management of the organization from theories of organizational behavior and management.

Tackling wicked problems in performance management and governance of public health: an empirical analysis of COVID-19 vaccination strategies

PurposePublic health strategies and activities are intrinsically complex. According to the literature, this “wickedness” depends on the different interests and expectations of the stakeholders and the community, the fragmented governance of the related services and the challenges in measuring and assessing public health outcomes. Existent performance measures and management systems for public health are not designed to cope with wickedness since they are mainly focused on inputs and outputs, neglecting broader outcomes because of their long-term impact and the poor accountability of results. This research aims to tackle this shortfall by adopting a dynamic performance management (DPM) approach.Design/methodology/approachThis research explores the case of the vaccination campaign of a Regional Health System. Through the analysis of an illustrative case study, the research discusses both opportunities and limits of the proposed approach.FindingsThis research highlights that DPM supports performance management (PM) in wicked contexts, thanks to the adoption of a system-wide perspective and the possibility of using simulation to experiment with alternative strategies and benchmarking performance results with simulated trends.Originality/valueThis article tackles a gap related to the management of wicked problems both from a theory and a practical perspective. In particular, this research suggests the adoption of DPM as an approach that may support policymakers in tackling social pluralism, institutional complexity and scientific uncertainty all at once.

Теоретическое обоснование выбора скоростного режима при ходовом тестовом экспресс-диагностировании агрегатов трансмиссии

The relevance of the study is determined by the need to solve the problem of operational management of the current technical condition of the rolling stock. Based on this, technical diagnostics activities become important because they allow you to quickly identify the current technical condition of the vehicle in question. At the same time, it is important, even at the stage of planning diagnostic measures, to choose such operational modes of movement along the test section that would ensure the best information content of the test runs. The theoretical substantiation of the choice of speed modes of arrivals of the studied vehicles along the test section of the road during express diagnostics was the purpose of this work. Research methods: analytical mechanics, differential methods, matrix calculus methods, mathematical numerical methods. The main results are in the proposal of a dynamic model of the vehicle transmission, which takes into account the disturbing effects from the engine and from the support base of the test section, where diagnostic runs are carried out. The amplitude-frequency characteristics of vibration accelerations of the vehicle body are calculated when it moves at given speeds along the simulated test diagnostic section. The practical significance of the study is confirmed by the results of the analysis of the obtained graphs, during which a conclusion was made about the most vibration-dangerous frequency ranges. This is important, since vibrations that occur at certain frequencies, which are directly dependent on the speed of movement, as a rule, cause the most intense responses in specific components and parts of transmission units. Further research is related to the theoretical substantiation of the choice of rational ranges of speed modes of the studied vehicles on the test diagnostic section of the support base, taking into account the characteristics and features of its surfaces. The results of the work are aimed at improving the system of maintenance and repair of the rolling stock of motor vehicles, namely, its diagnosis to determine the presence and degree of development of operational defects and damage, as well as the current technical condition of the transmission units.