Pareto Principle Research Articles

Dynamic reconfiguration for active distribution networks considering source and load uncertainties

ABSTRACT With the increasing penetration of distributed photovoltaic (PV) systems in active distribution networks (ADNs), the operation and control of these networks face new challenges, necessitating the urgent improvement of dynamic optimisation models and solution algorithms. To address this, this paper constructs a multi-objective dynamic reconfiguration model for distribution networks with integrated PV. The model accounts for the stochastic and time-sequential characteristics of source and load, aiming to optimise active network loss, average voltage deviation, and load balancing. To overcome the limitations of traditional multi-objective particle swarm optimisation (MOPSO), such as the tendency to fall into local optima and slow convergence in later stages, we introduce a hybrid multi-objective particle swarm optimisation (HMOPSO). This algorithm incorporates chaotic search and chicken swarm optimisation to enhance performance. This paper uses the Pareto principle to handle the multi-objective problem and applies a fuzzy membership function to identify the optimal compromise solution. The proposed model and algorithm were tested on an improved IEEE 33-node system. The results demonstrate the effectiveness of our approach, as it significantly improves the minimum node voltage while optimising the three specified objectives. This confirms the potential of the improved reconfiguration strategy for ADNs.

Pharmacoeconomic Analysis of Cosmetic Treatments on Seborrheic Dermatitis Using the 80/20 Method

Seborrheic dermatitis poses a persistent challenge for both patients and dermatologists, necessitating effective treatment strategies that address symptoms and provide long-term relief. This abstract explores the application of the Pareto Principle, also known as the 80/20 rule, in the development and utilization of cosmetics for managing seborrheic dermatitis. The Pareto Principle suggests that roughly 80% of outcomes result from 20% of inputs. In the context of seborrheic dermatitis treatment with cosmetics, this principle underscores the importance of identifying and prioritizing key ingredients and formulations that deliver the most significant therapeutic benefits. By leveraging the Pareto Principle, pharmacy managers can highlight the products which bring the highest profits in order to maximize profits. Furthermore, the Pareto Principle informs strategic marketing and distribution efforts, directing resources towards promoting and disseminating products that offer optimal efficacy and patient satisfaction. In conclusion, the application of the Pareto Principle in the treatment of seborrheic dermatitis with cosmetics offers a systematic framework for optimizing therapeutic outcomes and enhancing patient care.

Identification of the interconnections of components and major failure types of a longhole production system using Pareto principle: a case study of Bulyanhulu Gold Mine

The failures, which occur randomly, cause downtime in the individual components of the Longhole Production System (LHPS), lowering the reliability. In that case, the component interconnections and major failure types dominating the components of LHPS, an underground mining method, were reported in this article. The downtime data for 90 longhole stopes mined between April 2021 and March 2022 were collected at Bulyanhulu Gold Mine (BGM). The results show that the most common and practical interconnection of the components of LHPS is arranged in series. Furthermore, using the Pareto principle, 26, 30, and 9 major failure types were identified for the components of stope preparation, production and backfilling subsystems, respectively. Unlike other subsystems, no major failure type(s) were common to all components of the stope backfilling subsystem. The highest percentage (37.5%) of major failure types were related to equipment malfunction, 35.0% to ineffective human interventions, 20.0% to mine infrastructure malfunction, and 7.5% to variability in rock mass behaviour. It was noted that more than half of the components in each sub­system are major failing components. The major failing components in all quarters were drilling cable bolt holes, charging production holes, mucking, and paste fill pouring. Further study is needed with adequate data to investigate major failure types for bar­ricade construction.

Suppliers re-evaluation for tomorrow’s smart supply chain: AHP approach and performance criteria in automotive industry

The automotive sector has seen significant growth in recent years, with supply chain management becoming a key pillar for meeting evolving industry demands. Effective supply chain management relies heavily on material handling, impacting both inbound and outbound logistics. The study addresses the issue faced by automotive clients experiencing a decline in their quality KPIs due to non-compliant products delivered by suppliers. The focus is on identifying these suppliers, reclassifying them based on performance, and establishing key criteria for supplier re-evaluation, to address quality issues. We identify eight critical supplier selection criteria in the automotive sector. Supplier failures can lead to non-compliant raw materials, causing customer complaints and warranty returns due to undetected defects. The second part of the study involves reclassifying the suppliers of an automotive company with deteriorating quality KPIs. Using the Pareto principle and Lorenz curve, we identified the suppliers responsible for the majority of raw material deliveries. The Analytic Hierarchy Process (AHP) was used to reclassify suppliers based on quality criteria. The reassessment allowed us to identify underperforming suppliers who needed corrective action plans, or in some cases, exclusion in favor of suppliers meeting industry standards. This process involved meetings with the company's management team to define effective action plans aimed at improving quality performance. This approach will help automotive companies better align their supply chains with market demands, delivering value to customers while maintaining competitiveness. By optimizing supplier selection and reclassification, companies can reduce complaints, improve satisfaction, and enhance both the customer experience and production efficiency.

Application of the Pareto principle in the process of teaching a foreign language in a higher educational institution

Application of the Pareto principle in the process of teaching a foreign language in a higher educational institution

Crawler Crane Failure Cause Analysis Using Fishbone Diagram, Pareto Principle, and Failure Mode Effect Analysis: A Comprehensive Approach to Minimize Downtime and Improve Operational Reliability

Crawler cranes are critical heavy equipment in the construction industry, but they often experience failures that cause downtime and increased costs. This article comprehensively analyses crawler crane failures using three main methods: Fishbone Diagram, Pareto Principle, and Failure Mode and Effect Analysis (FMEA). Failure data for the past two years (January 2022 – September 2024) is analyzed to identify root causes and determine repair priorities. A Fishbone Diagram is used to identify the main causes of failure, which are grouped into four categories: Mechanical, Electrical, Environmental, and Human Error. From this analysis, it is found that mechanical failure is the most dominant cause. This analysis found that mechanical failure is the most dominant cause, mechanical failures account for most failures (60%), followed by electrical failures (33%), with failures in the gearbox and engine overheating being the most significant causes. Furthermore, FMEA evaluates potential failure modes, determines their impacts, and sets mitigation priorities based on the Risk Priority Number (RPN). The results of this study provide a strategic approach to minimize downtime by focusing maintenance efforts on the root causes of failure. This article also offers a new contribution by combining three comprehensive analysis methods not systematically applied to crawler crane maintenance. This research is expected to help improve operational reliability and reduce repair costs in the construction industry.

Whale optimization algorithm for production scheduling problems in small bakery enterprises

The no-wait flexible flowshop scheduling problem (NWFFSP) is a significant challenge in industries such as bakeries, where strict no-wait constraints and resource limitations, like oven availability, complicate scheduling. This research aims to evaluate the performance of the Whale Optimization Algorithm (WOA) in solving NWFFSP as a multi-objective problem, focusing on minimizing makespan and total oven idle time (ToIT). The study employs the Pareto principle to address trade-offs between these conflicting objectives. Experimental results demonstrate that WOA effectively balances both objectives, maintaining comparable efficiency to mono-objective optimization. The findings confirm WOA's potential as a robust tool for solving complex multi-objective scheduling problems in practical settings.

Subspace Collision: An Efficient and Accurate Framework for High-dimensional Approximate Nearest Neighbor Search

Approximate Nearest Neighbor (ANN) search in high-dimensional Euclidean spaces is a fundamental problem with a wide range of applications. However, there is currently no ANN method that performs well in both indexing and query answering performance, while providing rigorous theoretical guarantees for the quality of the answers. In this paper, we first design SC-score, a metric that we show follows the Pareto principle and can act as a proxy for the Euclidean distance between data points. Inspired by this, we propose a novel ANN search framework called Subspace Collision (SC), which can provide theoretical guarantees on the quality of its results. We further propose SuCo, which achieves efficient and accurate ANN search by designing a clustering-based lightweight index and query strategies for our proposed subspace collision framework. Extensive experiments on real-world datasets demonstrate that both the indexing and query answering performance of SuCo outperform state-of-the-art ANN methods that can provide theoretical guarantees, performing 1-2 orders of magnitude faster query answering with only up to one-tenth of the index memory footprint. Moreover, SuCo achieves top performance (best for hard datasets) even when compared to methods that do not provide theoretical guarantees.

The Pareto effect in tipping social networks: from minority to majority

Abstract. How do social networks tip? A popular theory is that a small minority can trigger population-wide social change. This aligns with the Pareto principle, a semi-quantitative law which suggests that, in many systems, 80 % of effects arise from 20 % of the causes. In the context of the transition to net-zero emissions, this vital 20 % can be a critical instigator of social tipping, a process which can rapidly change social norms. In this work, we asked whether the Pareto effect can be observed in social systems by conducting a literature review, placing a focus on social norm diffusion and complex contagion via social networks. By analysing simulation and empirical results of social tipping events across disciplines and a large parametric space, we identified consistent patterns across studies and key factors which help or hinder social tipping. We show evidence supporting a tipping point near 25 % of the total population within our compiled dataset. Near this critical mass, we observe a high likelihood for a social tipping event, where a large majority quickly adopts new norms. Our findings illustrate slight variations between modelling and empirical results, with average tipping points at 24 % and 27 %, respectively. Additionally, we show a range of critical masses where social tipping is possible; these values lie between 10 % and 43 %. These results indicate the potential, but not the inevitability, of rapid social change in certain susceptible populations and contexts. Finally, we provide practical guidance for facilitating difficult norm changes by (1) leveraging trusted community structures and building critical mass in clustered networks (particularly in the 10 %–43 % threshold range), (2) adapting strategies based on norm type and context, and (3) targeting groups with moderate preferences and network positions – avoiding reliance on highly central or well-connected individuals – to enable endogenous spread.

Pareto in Prison.

The Pareto principle is based on the concept that roughly 80% of outcomes are generated by 20% of inputs, efforts, or contributors within a group. Using a national sample of U.S. prison inmates, we examined various percentile rankings of self-reported institutional misconduct to determine how much disorder is created behind bars by the most prolific offenders. Findings revealed that, regardless of sex, the top 20% of inmates were responsible for approximately 90% of all rule violations and write-ups received. These general patterns remained similar even after adjusting infractions for time served in prison. Further analyses indicated that membership within these high-rate groups was often significantly predicted by those who were younger, black, had more extensive criminal histories, committed violent crimes, resided in state facilities, anticipated being released, used drugs prior to their arrest, were diagnosed with a personality disorder or ADHD, and exhibited worse negative affect. Some sex-specific effects were also observed. The disproportionate impact these chronic offenders have on the prison environment is detrimental to all individuals who live and work around them. Future research should investigate specific types of misconduct, distinct time intervals of incarceration, and facility effects such as management style, security levels, or offender composition.

SOLUTION OF A MULTICRITERIA ASSIGNMENT PROBLEM USING A CATEGORICAL EFFICIENCY CRITERION

Context. The paper considers a problem of assigning a set of employees to a finite set of operations in a multicriteria statement, under condition of a hierarchical structure of a partial efficiency criterion of performing a set of operations, being presented in such a way that each employee possesses a finite set of competencies and each operation has a finite set of characteristics. Numerical and categorical data types are provided for the use as exogenous parameters of the problem. The relevance of the assignment problem being considered is determined by an extremely wide range of practical applications, both in the classical statements and new modifications, the high demand for which is constantly generated by the dynamically developing economic environment. At the same time, a critically smaller number of scientific publications propose means of modeling and solving multi-criteria assignment problems, despite the importance of this type of problems in decision-making, both in theoretical and practical aspects. In general, in conditions of lack of information, the exogenous parameters of the problem cannot be specified in numerical form, therefore there is a need to use categorical data with further numerical coding. Objective. The goal of the work is to build a multicriteria mathematical model and, on this basis, carry out a numerical study of the optimization assignment problem, taking into account a hierarchical structure of a partial efficiency criterion of the selection of «operation – employee» pairs. Method. The study proposes a novel method of solving the assignment problem that implemented as a multi-stage process, which includes the stage of transformation of exogenous parameters of the model, given by categorical variables, based on the implementation of the Pareto principle and logistic mapping, the stage of constructing linear scalarization of the efficiency and the cost criteria.

Applying the Generalized Pareto Principle to Predict Peak Temperatures in Northeast Algeria

This study employs the Generalized Pareto Distribution (GPD) to model high temperature events at the Batna station, strategically applying varying thresholds to enhance accuracy and mitigate tail distribution bias. This was done by analyzing historical rainfall data from 1981 to 202. Using maximum likelihood estimation and an innovative approach to fitting multi-threshold GPDs, stable thresholds were established, particularly identifying the Pareto II type as the most suitable model for temperatures exceeding 25°C. Analysis revealed a consistent average temperature of 27.52°C, with a negative skewness indicating a bias toward lower values within extreme temperatures. The study also predicts return levels for different periods, providing critical temperature thresholds expected to be exceeded every 2, 20, 50, and 100 years. These findings contribute to understanding extreme temperature dynamics in the region, supporting urban planning, infrastructure design, and climate resilience strategies.

Risk mitigation analysis of delays in the procurement of personal protective equipment using the house of risk method

PT XYZ is a shipping company that provides sea transportation services, including ship rental and ship management. In its business operations, PT XYZ requires Personal Protective Equipment (PPE) procurement, which faces challenges due to high urgency and frequently changing order lead times, leading to delays in PPE delivery by suppliers. This study aims to apply the House of Risk (HOR) technique to analyze risk agents (risk causes) related to procurement risks and to identify and measure the impact of these risks on the procurement of PPE. The study identified 20 risk events and 20 risk agents. In HOR Phase 1, risk agents were analyzed using the Aggregate Risk Potential (ARP) approach, with a Pareto diagram applying the 80:20 principle to prioritize the most dominant risk agents. In HOR Phase 2, six handling strategies were developed, and the 60:40 Pareto principle was used to select the top four primary mitigation strategies based on their effectiveness. The results indicate three dominant risk agents among the 20 identified, along with four prioritized mitigation strategies out of the six developed strategies. These strategies are expected to improve the timeliness and efficiency of PPE procurement in PT XYZ’s operations.

Renewable realities: Charting a greener course for the world's high‐emitting nations through information technology insights

AbstractCarbon dioxide (CO₂) is the most abundant gas among all greenhouse gas emissions, severely impacting global warming. This study examines the impact of Information and Communication Technology (ICT), population dynamics, Per Capita Gross Domestic Product (PGDP), and Renewable Energy Consumption (REC) on CO₂ on a global scale, representing 38 countries selected using the Pareto principle. Results from the panel regression model indicate a significantly positive relationship between ICT, PGDP, and population on CO₂ emissions. In contrast, REC exhibits a negative relationship. The Multiple Linear Regression model shows that an increase in PGDP leads to higher CO₂ emissions, except in Uzbekistan. ICT increases emissions in the United States, Argentina, Australia, Canada, and Egypt. Population growth raises emissions, except in the United States, France, Germany, and Russia. REC reduces CO₂ emissions in most countries. Policymakers in individual countries can gain a precise understanding of how these variables impact CO₂ emissions, enabling them to mitigate the risks associated with global warming.

Professionally significant qualities of teaching producing in the context of digital development: Evaluating the effectiveness by education stakeholders

Introduction. The article is devoted to the problem of increasing the level of communicative culture in future economists in the digital era. The purpose of the research is to substantiate the effectiveness of professionally important qualities of teaching producing in universities of Economics, taking into account the digital format of interaction. Materials and Methods. The methodological basis of the study is the Pareto optimality principle (2080), which allows the authors to determine the necessary minimum of teaching resources in terms of modern communication knowledge for training economists in the digital age. During the study, an online survey was conducted in order to substantiate the effectiveness of professionally important qualities of teaching producing in the context of the digital specifics of the socio-economic space. The research sample consisted of students and academic staff of economics departments of the Financial University under the Government of the Russian Federation, Omsk State Pedagogical University, and Omsk State Technical University. Results. The theoretical analysis of the research problem revealed professionally important qualities of teaching producing (communication skills, digitals kills, knowledge of the principles of teaching ethics to create an atmosphere of trust and psychological safety), which facilitate the development of future economists’ communicative culture (motivational, cognitive, and functional components). According to the results of the empirical part of the study, the education stakeholders highly appreciated the effectiveness of professionally significant qualities of teaching producing and their positive correlation. Conclusions. The use of the Pareto rule allows the authors to conclude that the formation of professionally significant t qualities of teaching producing, which make up about 20% of the professional qualities composition for academic staff at universities of economics, determines 80% of the productivity of educational outcomes in terms of developing future economists’ communicative culture. This, in turn, determines the ability of graduates to build communication taking into account the career prospects at various levels of digitalization and interaction with artificial intelligence systems.

UAV path planning based on improved dung beetle algorithm with multiple strategy integration

This research presents a multi-strategy augmented dung beetle algorithm (CDBO) for UAV path planning in intricate 3D environments. Its main objective is to address the path planning challenge by formulating an integrated cost function model and environment representation that aligns the optimisation task with the navigation prerequisites and safety constraints of the UAV. Firstly, the algorithm initialises the particle population based on the Lévy flight principle to improve the species diversity and adequately search the solution space. Subsequently, an exponentially decreasing inertia weighting strategy is introduced to improve the convergence speed of the algorithm. In addition, the algorithm uses an adaptive [Formula: see text]-distribution with perturbed variation of the updated positions so that the algorithm avoids falling into a local optimum. Finally, to enhance the robustness of the system, the algorithm incorporates an elite retention strategy based on the Pareto principle. In this study, rigorous tests using 12 CEC2022 test functions and Wilcoxon rank sum test are conducted as benchmarks for the performance of the algorithm. The results show that the enhanced dung beetle algorithm outperforms the traditional algorithm, highlighting its efficiency and robustness. In addition, the efficacy of the enhanced dung beetle algorithm was validated in a variety of complex 3D environments, affirming its ability to generate optimal paths. This study further highlights the importance of effective algorithms in UAV path planning, addressing the key issue of optimising flight operations in intricate spatial scenarios.

Comprehensive Statistical Analysis of ISSN Records

The history of the origin and transformation of the ISSN Register is considered, and all publications available through Google Scholar and Semantic Scholar on the number of ISSN records and their dynamics are collected together. Data on the number of entries in the ISSN Register by country for 2014 and 2021 is presented, along with the seven-year increase in these entries in comparison with similar data for 1991 through 1998. From these data, the top ten countries were analyzed based on the maximum increase in records over these two seven-year periods. It is shown that the first list of countries with the maximum increase in the number of ISSN records for 2014 through 2021 included exclusively developing countries, and the second list (1991–1998) included mainly developed countries. Similar increases in the number of ISSN records were analyzed for the languages of serial publications and it was shown that in both language lists there was only the Turkish language and the leading European languages were absent. It is shown that the total contributions of ISSN records of leading countries and languages to the total number of ISSN records satisfy the Pareto principle for all years studied. The calculations were made on the indices of linguistic liberalization of the information space of states and information and linguistic influence (or language expansion) according to ISSN indicators. It is shown that aggregating countries by language has made it possible to significantly reduce the discrepancy between the total ISSN records for countries in which a particular language predominates and the ISSN records for a given language. These differences for calculations for 2014 and 2021 levels did not exceed 9% for English, Spanish and Portuguese, and 14% for French, which corresponds to the languages of former colonial empires. In conclusion, a linear regression relationship between ISSN/10 thousand people and GDP per capita with moderate values of the correlation coefficient was obtained in two versions, which indirectly confirms the Constancy Hypothesis.

The Role of the Pareto Principle in Quality Management within Industry 4.0: A Comprehensive Bibliometric Analysis

Quality is a fundamental aspect of the management of almost every area of a company, directly influencing the efficiency of its processes. The increased importance of quality, as well as advances in industrialisation methods and computerisation, has stimulated the development of a new generation of technologies, leading to the fourth industrial revolution known as Industry 4.0. In addition to new technologies, the Pareto principle plays an important role in quality management, enabling the identification of the key factors that influence quality, emphasising that 20% of causes are responsible for 80% of quality problems. Its importance has been highlighted by the American Society for Quality (ASQ), which recognises the Pareto principle as one of the seven basic tools used in the area of process improvement. The purpose of this study is to identify the impact of the Pareto principle on quality management on the basis of a bibliometric analysis carried out to characterise the evolutionary aspects of the development of key terms specific to the area under consideration. The analysis focuses on a sample of 8002 items, and the data collected come from the extensive Scopus database of scientific articles, covering the years 1990-2024. VOSviewer software was used as a tool. On the basis of the empirical data, the exponential growth of the number of publications was confirmed in terms of the relationship between the Pareto principle and quality management. On the basis of the resulting visualisation maps, five areas (clusters) were identified and characterised in terms of keyword coincidence, and their evolutionary natures were described. This publication can serve as a basis for further considerations in the impact layer of the Pareto principle in terms of quality management.

Incommensurability, the sequence argument, and the Pareto principle

Parfit (Theoria 82:110–127, 2016) responded to the Sequence Argument for the Repugnant Conclusion by introducing imprecise equality. However, Parfit’s notion of imprecise equality lacked structure. Hájek and Rabinowicz (2022) improved on Parfit’s proposal in this regard, by introducing a notion of degrees of incommensurability. Although Hájek and Rabinowicz’s proposal is a step forward, and may help solve many paradoxes, it can only avoid the Repugnant Conclusion at great cost. First, there is a sequential argument for the Repugnant Conclusion that uses weaker and intuitively more compelling assumptions than the Sequence Argument, and which Hájek and Rabinowicz’s proposal only undermines, in a principled way, by allowing for implausible weight to be put on the disvalue of inequality. Second, if Hájek and Rabinowicz do put such implausible weight on the disvalue of inequality, then they will have to accept that a population A is not worse than another same sized population B even though everyone in B is better off than anyone in A.

WHO Surgical Safety Checklist compliance rate at a large tertiary hospital in Vietnam.

The WHO Surgical Safety Checklist has been instrumental in reducing surgical deaths by 47% globally since its inception in 2009. A study was conducted to assess the compliance of hospital staff with the Surgical Safety Checklist and identify potential barriers to its implementation at a large tertiary public hospital in Vietnam. The study analysed 135 surgical cases between February and September 2021 using the Pareto principle with eight error categories, including (1) patient identification, (2) equipment, (3) risk management, (4) blood loss, (5) allergy, (6) items left inside the patient, (7) surgical specimens and (8) patient safety and recovery management. Compliance with the Surgical Safety Checklist was between 77% and 93%, with five categories accounting for more than 80% of errors. Periodic monitoring and staff training can improve compliance and help reduce errors for better patient safety. Long-term solutions addressing infrastructure challenges are also crucial.