Allocation Of Points Research Articles

Dual-objective economic planning of simultaneous allocation of disconnectors and maneuvering points considering the direction of error reduction in the presence of fault detector with the multi-objective PSO

Dual-objective economic planning of simultaneous allocation of disconnectors and maneuvering points considering the direction of error reduction in the presence of fault detector with the multi-objective PSO

ИНСТРУМЕНТЫ ИССЛЕДОВАНИЯ ЦИФРОВОЙ УСТОЙЧИВО-СТИ МУНИЦИПАЛЬНЫХ ОБРАЗОВАНИЙ МОНОПРОФИЛЬНОГО ТИПА ДЛЯ ФОРМИРОВАНИЯ НОВЫХ ТОЧЕК РЕГИОНАЛЬНОГО РОСТА

In the article, special attention is paid to the diverse aspects of the allocation of regional growth points, which made it possible to identify their characteristic features and parameters of assessing factors for a possible rating of territories. It was concluded that the methodological and methodological aspects of the study of regional development parameters encountered in practice for identifying growth points do not take into account such important characteristics as the dig-ital development of single-industry territories, digital sustainability and digital transformation processes that take place in a particular territory. At the same time, there is no unified terminology that allows taking into account the peculiar-ities of digitalization of municipalities, which was the basis for the proposal of the author's concepts "digital transformation of a single-profile municipal for-mation" and "digital stability of a single-profile municipal formation", as well as the proposal of a system of parameters for their assessment. A register of prob-lematic aspects of the allocation of regional growth points has been formed, which are subject to monitoring analytical treatments for the use of appropriate tools to suppress them.

Empathy incites a stable prosocial decision bias.

Empathy toward suffering individuals serves as potent driver for prosocial behavior. However, it remains unclear whether prosociality induced by empathy for another person's pain persists once that person's suffering diminishes. To test this, participants underwent functional magnetic resonance imaging while performing a binary social decision task that involved allocation of points to themselves and another person. In block one, participants completed the task after witnessing frequent painful stimulation of the other person, and in block two, after observing low frequency of painful stimulation. Drift-diffusion modeling revealed an increased initial bias toward making prosocial decisions in the first block compared with baseline that persisted in the second block. These results were replicated in an independent behavioral study. An additional control study showed that this effect may be specific to empathy as stability was not evident when prosocial decisions were driven by a social norm such as reciprocity. Increased neural activation in dorsomedial prefrontal cortex was linked to empathic concern after witnessing frequent pain and to a general prosocial decision bias after witnessing rare pain. Altogether, our findings show that empathy for pain elicits a stable inclination toward making prosocial decisions even as their suffering diminishes.

Simultaneous allocation of soft open points and tie switches in harmonic polluted distribution networks

The growing power quality issues stemming from the higher presence of converter-based appliances in the distribution network increases the harmonic risks. Given the importance of tackling these issues to deliver high-quality power to customers, this investigation provides a promising approach focused on effectively designating soft open points (SOPs) and tie switches in the distribution networks. The objectives of this investigation include the reduction of total harmonic distortion (THD), power loss per various harmonic frequencies and the number of SOPs. To evaluate the performance of the proposed approach, the study is carried out on two well-known networks, 33-bus, and 69-bus. Through these analyses, it was shown how effectively THD, power loss, and voltage profiles are improved when SOPs and tie switches are allocated together. The outcomes of thorough analyses provide credence to the assertion that the suggested approach is very promising for mitigating power quality issues by handling uncertainties in loads by Monte Carlo Simulation (MCS). In more detail, the obtained solutions assure that the suggested method has superior power quality across the networks by maintaining the THD levels within the standard margins. Additionally, the developed model offers advantages including reduced power loss and enhanced voltage profiles, which increase the overall network efficiency, while reducing the total investment cost by reducing the number of SOPs and power loss in power distribution networks.

Sum rate maximization in UAV-assisted data harvesting network supported by CF-mMIMO system exploiting statistical CSI

Unmanned Aerial Vehicles (UAVs) have been considered to have great potential in supporting reliable and timely data harvesting for Sensor Nodes (SNs) from an Internet of Things (IoT) perspective. However, due to physical limitations, UAVs are unable to further process the harvested data and have to rely on terrestrial servers, thus extra spectrum resource is needed to convey the harvested data. To avoid the cost of extra servers and spectrum resources, in this paper, we consider a UAV-based data harvesting network supported by a Cell-Free massive Multiple-Input-Multiple-Output (CF-mMIMO) system, where a UAV is used to collect and transmit data from SNs to the central processing unit of CF-mMIMO system for processing. In order to avoid using additional spectrum resources, the entire bandwidth is shared among radio access networks and wireless fronthaul links. Moreover, considering the limited capacity of the fronthaul links, the compress-and-forward scheme is adopted. In this work, in order to maximize the ergodically achievable sum rate of SNs, the power allocation of ground access points, the compression of fronthaul links, and also the bandwidth fraction between radio access networks and wireless fronthaul links are jointly optimized. To avoid the high overhead introduced by computing ergodically achievable rates, we introduce an approximate problem, using the large-dimensional random matrix theory, which relies only on statistical channel state information. We solve the nontrivial problem in three steps and propose an algorithm based on weighted minimum mean square error and Dinkelbach's methods to find solutions. Finally, simulation results show that the proposed algorithm converges quickly and outperforms the baseline algorithms.

Building the workforce of tomorrow: The weighting of rural exposure in standardised curriculum vitae scoring criteria for entrance into Australian specialty training programs.

To determine the weighting of rural exposure within publicly available standardised curriculum vitae (CV) scoring criteria for trainee medical officer's applying into medical and surgical specialty training programs in Australia and New Zealand. An observational analysis of rural exposure point allocations within publicly available standardised CV scoring criteria for entrance into specialty training programs. All Australian and New Zealand medical and surgical specialties training programs outlined by the Australian Health Practitioner Regulation Agency (AHPRA) who publish publicly available standardised CV scoring criteria for entrance into specialty training were included. Of the 14 specialty training programs that publish publicly available standardised CV scoring criteria, 8/14 allocate points towards rural exposure. While the allocation of points within this scoring domain varies between the eight training programs, the mean weighting of rural exposure is 13.7%. The relative weighting of rural exposure varies between the eight specialty training programs who include rural exposure as a CV scoring criteria. The deliberate and strategic construction of CV scoring criteria and inclusion of rural exposure points is important to continue developing the Australian rural specialist workforce. Future development of standardised CV scoring criteria should continue to consider point allocation towards rural exposure and related activities to ensure that the requirements of rural Australian healthcare needs are met across medical and surgical specialties.

Density peaks clustering based on superior nodes and fuzzy correlation

The Density Peaks Clustering (DPC) algorithm is simple and efficient, but still has a few limitations. For example, DPC needs manual selection of clustering centers and may miss the correct cluster when searching for denser nearest neighbors, which may cause incorrect allocation of data points. To address these limitations, this work proposes a novel density peaks clustering algorithm based on superior nodes and fuzzy correlation (DPC-SNFC). Reverse nearest neighbors are used first to find the nearest point with a higher density as the superior node. Fuzzy correlation is then applied to construct connectivity subgraphs without using clustering centers. The connectivity subgraphs can identify the different clusters. Extensive experiments are conducted using 12 synthetic datasets and 10 real datasets and using 6 state-of-the-art baseline algorithms. The experimental results show that the proposed DPC-SNFC algorithm outperforms the baseline algorithms, which validates its efficiency.

Technical note: Comparing three different methods for allocating river points to coarse-resolution hydrological modelling grid cells

Abstract. The allocation of points in a river network to pixels of a coarse-resolution hydrological modelling grid is a well-known issue, especially for hydrologists who use measurements at gauging stations to calibrate and validate distributed hydrological models. To address this issue, the traditional approach involves examining grid cells surrounding the considered river point and selecting the best candidate, based on distance and upstream drainage area as decision criteria. However, recent studies have suggested that focusing on basin boundaries rather than basin areas could prevent many allocation errors, even though the performance gain is rarely assessed. This paper compares different allocation methods and examines their relative performances. Three methods representing various families of methods have been designed: area-based, topology-based and contour-based methods. These methods are implemented to allocate 2580 river points to a 1 km hydrological modelling grid. These points are distributed along the entire hydrographic network of the French southeastern Mediterranean region, covering upstream drainage areas ranging from 5 to 3000 km2. The results indicate that the differences between the methods can be significant, especially for small upstream catchment areas.

ALIKE-APPLE: A Lightweight Method for the Detection and Description of Minute and Similar Feature Points in Apples

Current image feature extraction methods fail to adapt to the fine features of apple image texture, resulting in image matching errors and degraded image processing accuracy. A multi-view orthogonal image acquisition system was constructed with apples as the research object. The system consists of four industrial cameras placed around the apple at different angles and one camera placed on top. Following the image acquisition through the system, synthetic image pairs—both before and after transformation—were generated as the input dataset. This generation process involved each image being subjected to random transformations. Through learning to extract more distinctive and descriptive features, the deep learning-based keypoint detection method surpasses traditional techniques by broadening the application range and enhancing detection accuracy. Therefore, a lightweight network called ALIKE-APPLE was proposed for surface feature point detection. The baseline model for ALIKE-APPLE is ALIKE, upon which improvements have been made to the image feature encoder and feature aggregation modules. It comprises an Improved Convolutional Attention Module (ICBAM) and a Boosting Resolution Sampling Module (BRSM). The proposed ICBAM replaced max pooling in the original image feature encoder for downsampling. It enhanced the feature fusion capability of the model by utilizing spatial contextual information and learning region associations in the image. The proposed BRSM replaced the bilinear interpolation in the original feature aggregator for upsampling, overcoming the apple side image’s geometric distortion and effectively preserving the texture details and edge information. The model size was shrunk by optimizing the number of downsampling operations from the image encoder of the original model. The experimental results showed that the average number of observed keypoints and the average matching accuracy were improved by 166.41% and 37.07%, respectively, compared with the baseline model. The feature detection model of ALIKE-APPLE was found to perform better than the optimal SuperPoint. The feature point distribution of ALIKE-APPLE showed an improvement of 10.29% in average standard deviation (Std), 8.62% in average coefficient of variation (CV), and 156.12% in average feature point density (AFPD). Moreover, the mean matching accuracy (MMA) of ALIKE-APPLE improved by 125.97%. Thus, ALIKE-APPLE boasts a more consistent allocation of feature points and greater precision in matching.

Review of Māori equity in surgical trainee selection.

The Royal Australasian College of Surgeons (RACS) aims to achieve Māori health equity and cultural safety within the surgical workforce. The RACS Māori Health Strategy and Action Plans encourage Surgical Education and Training (SET) selection criteria that recognizes and credit applicants who identify as Māori or demonstrate competence in Māori health issues. This study investigates the current SET selection criteria for Māori entering surgical specialties. The selection criteria for each surgical speciality for the proposed 2024 intake were examined through a documentary analysis. Criteria were reviewed for applicability to Māori identification and/or cultural competency. Criteria related to Māori identification and/or cultural competency make up 6%, 2%, and 1.5% of Otolaryngology and Head and Neck, General, and Vascular Surgery total SET selection score respectively. Criteria related to Māori identification and/or cultural competency make up 9% and 0.1% of Orthopaedic and Plastics and Reconstructive Surgery ranking scores for interview eligibility respectively. Cardiothoracic Surgery, Paediatric Surgery, Neurosurgery and Urology specialties do not incorporate any criteria appertaining to Māori. Allocation of research-related points determined by authorship may disincentivize Māori trainees. Some surgical specialties fail to recognize or credit Māori identification and cultural competency in SET selection criteria. There is a need for regular auditing to ensure SET criteria align with the RACS aspirations for Māori health equity and cultural safety within the surgical workforce.

Creatinine-Based Definition of Kidney Disease in the Charlson Comorbidity Index May Underestimate Prognosis in Males Compared to an Estimated Glomerular Filtration Rate Definition.

(1) Background: The Charlson comorbidity index allocates two points for chronic kidney disease (CKD) if serum creatinine is above 3.0 mg/dL (270 µmol/L). However, contemporary CKD staging is based on the estimated glomerular filtration rate (eGFR) derived from population-based equations. The aim of this study was to determine the correlation between eGFR and the creatinine threshold of the Charlson comorbidity index for defining CKD. (2) Methods: We conducted a cross-sectional study of 664 patients with established CKD attending general nephrology clinics over 6 months. Dialysis patients and kidney transplant recipients were excluded. (3) Results: The median age was 68 years, and 58% of the participants were male. By modeling with fractional polynomial regression, we estimated that a creatinine of 270 µmol/L corresponded with an eGFR of 14.8 mL/min/1.73 m2 for females and 19.4 mL/min/m2 for males. We also estimated that an eGFR of 15 mL/min/1.73 m2 (threshold which defines Stage 5 CKD) corresponded to a serum creatinine of 275 µmol/L for females and 342 µmol/L for males. After applying these sex-specific creatinine thresholds, 39% of males and 3% of females in our CKD study population who scored points for CKD in the Charlson comorbidity index had not yet reached Stage 5 CKD. (4) Conclusions: There is a significant difference in the creatinine threshold to define Stage 5 CKD between males and females, with a bias for greater allocation of Charlson index points for CKD to males despite similar eGFR levels between the sexes. Further research could examine if replacing creatinine with eGFR improves the performance of the Charlson comorbidity index as a prognostic tool.

Disseminating health research to public health policy-makers and practitioners: a survey of source, message content and delivery modality preferences

BackgroundUnderstanding the views of policy-makers and practitioners regarding how best to communicate research evidence is important to support research use in their decision-making.AimTo quantify and describe public health policy-makers and practitioners’ views regarding the source, content and form of messages describing public health research findings to inform their decision-making. We also sought to examine differences in preferences between public health policy-makers and practitioners.MethodsA cross sectional, value-weighting survey of policy-makers and practitioners was conducted. Participants were asked to allocate a proportion of 100 points across different (i) sources of research evidence, (ii) message content and (iii) the form in which evidence is presented. Points were allocated based on their rating of influence, usefulness and preference when making decisions about health policy or practice.ResultsA total of 186 survey responses were received from 90 policy-makers and 96 practitioners. Researchers and government department agencies were the most influential source of research evidence based on mean allocation of points, followed by knowledge brokers, professional peers and associations. Mean point allocation for perceived usefulness of message content was highest for simple summary of key findings and implications, and then evidence-based recommendations and data and statistical summaries. Finally, based on mean scores, policy-makers and practitioners preferred to receive research evidence in the form of peer-reviewed publications, reports, evidence briefs and plain language summaries. There were few differences in scores between policy-makers and practitioners across source, message content or form assessments or those with experience in different behavioural areas.ConclusionsThe findings should provide a basis for the future development and optimization of dissemination strategies to this important stakeholder group.

Bi-objective robust planning model for optimal allocation of soft open points in active distribution network: A flexibility improvement approach

Improving system flexibility is one of the requirements of today's power grids in response to existing uncertainties and fluctuations. High penetration of renewable energy sources (RESs) poses many technical challenges to the system, making it difficult to solve unless flexibility is provided by network-side tools efficiently. In this regard, this paper uses the possibility of changing the network topology in the optimal presence of intelligent switching tools, such as soft open points (SOPs), to improve the network's operational flexibility. The penetration capacity range of RESs is defined as an index to evaluate the active distribution network (ADN) flexibility considering the different operating conditions caused by the inherent uncertainty of RESs. The more compatible a network is with a larger penetration capacity range of RESs without violating system security and power flow constraints, the more flexible the network will be in dealing with the uncertain production of such sources. The optimal site and size of SOPs, final network topology, and penetration capacity range of RESs are determined by solving a bi-objective robust optimization model cost-effectively and in a flexibility improvement approach while considering supply-side uncertainty. The proposed model is conducted on IEEE 33-bus system, and the results are presented and discussed.

MEAT PRODUCTION INDUSTRIES OF KAZAKHSTAN AND RUSSIA: COMPARATIVE ANALYSIS AND TRENDS DEVELOPMENT

The purpose of the study. To analyze the state of meat production in the Republic of Kazakhstan and the Russian Federation with the allocation of promising points of balanced growth and sustainable development in order to form clear prerequisites for improving the quality of nutrition of the population of these countries.Methodology. The following scientific methods are used in the work: statistical observation; comparative analysis; meta-analysis; multidimensional statistical analysis; analogy; synthesis; formalization; summary and grouping of statistical observation materials; absolute and relative statistical values; expert evaluation; retrospective.The originality / value of the research is to identify promising directions for the development and sustainable growth of the sectoral sectors of the agro-industrial complex (AIC) of the Republic of Kazakhstan and the Russian Federation.Findings. Today in the Russian Federation and the Republic of Kazakhstan, a large number of industry programs have been approved and are being implemented quite successfully, aimed at ensuring the sustainable and effective development of meat-product subcomplexes; promising forms of organization of the industry market are: contracting of raw materials; sale of products at wholesale sites; sale through commodity distribution networks of farmers' cooperation; supplies at the intersectoral level; stock exchanges; sale from farms; in Kazakhstan today, feed is produced almost 2 times less than the zootechnical norm; specialized enterprises for fattening cattle, sheep, pigs and poultry should become the basis of the meat industry of Kazakhstan; specialization, compared with diversified production, provides 1.5-2 times higher productivity and reduces the cost of livestock production by 25-40% in Kazakhstan; mechanized shepherd brigades should become the main organizational form of lamb production in steppe, semi-desert areas; one of the most significant risks in the development of modern animal husbandry in Russia is the threat of the spread of dangerous and especially dangerous diseases among; today in the Russian Federation there is a serious spread between the initial price of agricultural producers and the final price in the retail segment for meat products; the level of resource provision in the Russian Federation has quite high indicators and a steady growth trend is inherent in it; today the industry sector in Russia is functioning steadily, and the points of growth should be: export; entrepreneurship; investment; digitalization; veterinary control; the basis for the sustainable development of the industrial sectors of the Republic of Kazakhstan and the Russian Federation should be specialized enterprises for fattening cattle, sheep, pigs and poultry.

An optimal experimental design strategy for improving parameter estimation in stochastic models

Systematic model-based design of experiment is essential to maximise the information from an experimental campaign. This technique is even more important to design experiments in systems described by stochastic models where the information quantity is characterised by intrinsic uncertainty, which has a significant impact on the experimental design for yielding informative data for precisely estimating model parameters. In this work, a new method for stochastic model-based design of experiments (SMBDoE) is presented to simultaneously identify the optimal operating conditions and the allocation of sampling points in time. The optimal experiment is identified by two sampling strategies selecting sampling intervals based on the average and the uncertainty of Fisher information. Seed coating is used as a case study to illustrate the feasibility of the method in identifying optimal coating conditions and sampling strategy in an industrial application.

Integrated mathematical optimisation approach for the tower crane hook routing problem to satisfy material demand requests on-site

Optimising decisions around the location and operation of tower cranes can improve the workflow in construction projects. Traditionally, the location and allocation problems involved in tower crane operations in the literature have been solved separately from the assignment of material supply points to demand points and the scheduling of the crane’s activity sequence across supply and demand points on a construction site. To address the gap, this paper proposes a binary integer programming problem, where location of the tower crane, allocation of supply points to material-demanding regions, and routing of hook of the crane based on activity sequencing of the hook across supply and material-demanding regions on site are optimised. The novelty in this work is in the way the crane’s activity scheduling is modelled via mathematical programming, based on routing the hook movement to meet material demand, through minimising tower crane operating costs. A realistic case study is solved to assess the validity of the model. The model is contrasted with results obtained from other solving algorithms commonly adopted in the literature, along with a solution proposed by an experienced practitioner. Results indicate that all instances can be solved when compared to other meta-heuristics that fail to achieve an optimum solution. Compared to the solution proposed by the practitioner, the results of the proposed model achieve a 46% improvement in objective function value. Planners should optimise decisions related to the location of the crane, the crane’s hook movement to meet service requests, and supply points’ locations and assignment to material-demanding regions simultaneously for effective crane operations.

Monitoring European data with prospective space–time scan statistics: predicting and evaluating emerging clusters of COVID-19 in European countries

BackgroundCoronavirus disease 2019 (COVID-19) has become a pandemic infectious disease and become a serious public health crisis. As the COVID-19 pandemic continues to spread, it is of vital importance to detect COVID-19 clusters to better distribute resources and optimizing measures. This study helps the surveillance of the COVID-19 pandemic and discovers major space–time clusters of reported cases in European countries. Prospective space–time scan statistics are particularly valuable because it has detected active and emerging COVID-19 clusters. It can prompt public health decision makers when and where to improve targeted interventions, testing locations, and necessary isolation measures, and the allocation of medical resources to reduce further spread.MethodsUsing the daily case data of various countries provided by the European Centers for Disease Control and Prevention, we used SaTScan™ 9.6 to conduct a prospective space–time scan statistics analysis. We detected statistically significant space–time clusters of COVID-19 at the European country level between March 1st to October 2nd, 2020 and March 1st to October 2nd, 2021. Using ArcGIS to draw the spatial distribution map of COVID-19 in Europe, showing the emerging clusters that appeared at the end of our study period detected by Poisson prospective space–time scan statistics.ResultsThe results show that among the 49 countries studied, the regions with the largest number of reported cases of COVID-19 are Western Europe, Central Europe, and Eastern Europe. Among the 49 countries studied, the country with the largest cumulative number of reported cases is the United Kingdom, followed by Russia, Turkey, France, and Spain. The country (or region) with the lowest cumulative number of reported cases is the Faroe Islands. We discovered 9 emerging clusters, including 21 risky countries.ConclusionThis result can provide timely information to national public health decision makers. For example, a country needs to improve the allocation of medical resources and epidemic detection points, or a country needs to strengthen entry and exit testing, or a country needs to strengthen the implementation of protective isolation measures. As the data is updated daily, new data can be re-analyzed to achieve real-time monitoring of COVID-19 in Europe. This study uses Poisson prospective space–time scan statistics to monitor COVID-19 in Europe.

Image copy-move forgery detection based on dynamic threshold with dense points

Copy-move tampering is one of the most popular tampering techniques at present. The tampered region of the image has good fusion with the original image, which increases the difficulty of detection. After years of research, the current detection method based on key points still has the following problems: 1) Failure to achieve forgery detection of small areas/self-similar areas/smooth areas, 2) Lack of reasonable feature point extraction methods, 3) The various stages of copy-move forgery detection (CMFD) work are relatively independent and lack close connections, 4) A fixed threshold is used as the region of interest similarity metric in the matching and localization stages. The failure to consider tampered images and the diversity of tampered regions leads to the limited detection capability of the algorithm. Considering the actual situation of tampering with the picture, to solve the above problems, we propose a copy-move forgery detection method based on the dynamic threshold. First, we determine the point extraction strategy in each super pixel block according to the size of the simple line interface calculation (SLIC) super pixel block and the Weber local descriptor (WLD) descriptor to ensure the reasonable allocation of feature points and reduce unnecessary points. These key points are then characterized by the scaling, flip and rotation invariants of the fractional general Jacobi-Fourier moments (FJFMs). Then, the matching and mismatch filtering thresholds of each feature point are determined through the WLD and SLIC features, and the SLIC feature is used to replace the distance threshold to improve the detection accuracy of small manufacturing areas. Finally, based on the matching results and SLIC features, an effective positioning method is proposed to improve the speed and accuracy of positioning. Experimental results show that the proposed algorithm is superior to the classic methods in recent years in terms of time and accuracy.

On the theoretical and methodological foundations of the study of secular and confessional education

The article analyzes the qualitative and temporal configuration of secular and confessional education with the allocation of positive aspects and critical points. According to the authors, a comparative analysis of the theoretical and methodological foundations of the educational models under consideration acts as a platform for understanding the pedagogical experience as a whole, and provides for the selection of a wide variety of options analyzed in close relationship with the genesis of culture, science, and social thought. Carrying out a study of the particular specifics of the functioning of models of secular and confessional education implemented in various world educational practices, the authors came to the conclusion that there is a kind of “coordinate system” that determines the nature of existing models. This coordinate system includes the historical specifics of the existing relationships between state institutions and religious associations; the peculiarities of national and cultural traditions of modern European countries and Kazakhstan; the role and place of religious values in the life of the people; the nature of legal regulation in the field of educational practices of secular and religious institutions. Keywords: education, secular model of education, confessional model of education, dialogue of cultures.

Optimal Recloser Placement in Distribution System Considering Maneuver Points, Practical Limitations, and Recloser Malfunction

Improving reliability is one of the most critical problems in power distribution networks. Optimal placement of automatic switches improves system reliability. Practical constraints such as maneuver points and the capacity of neighboring feeders are often overlooked. Reliability indices may also be improved by optimizing maneuver point locations considering the capacities of neighboring feeders. In this paper, a new perspective on the problem of recloser placement in the presence of switch disconnectors (sectionneurs) with the ability to disconnect under load is proposed. The limitations of transmission power capacity at maneuver points are also considered in the proposed method. In addition, by proposing a Markov model, the possibility of malfunction of reclosers is considered. The proposed method is applied to two case studies including Roy Billinton Test System (RBTS) and the real distribution network in Mazandaran, Iran. Real system data are collected during the years 2016–2021. The problem is solved for various scenarios. In the case of 12 fully reliable reclosers, taking into account the optimal maneuver points and without any capacity limitations, compared to the allocation of maneuver points at the endpoints of the feeders show a %4.37 increase in the reliability of the real system. Even by considering practical capacity limitations in the maneuver points, this improvement is %3.47. Also, the results show a %6.684 decrease in the system reliability by considering malfunction in the case of 12 reclosers. This underscores the importance of taking into account the reclosers malfunctions in optimal switch placement for better decision making in practice.