Elite Replacement Research Articles

Multi-objective reactive power optimization for low voltage distribution networks based on improved marine predator algorithm

A large number of distributed photovoltaic generators are constructed in the 0.4 kV distribution network, which causes the distribution network’s power flow and voltage amplitude to change, and brings new challenges to the reactive voltage control. Firstly, a reactive power adjustment model is invented, and the objective of the optimization is to minimize the distribution network line losses and node voltage shifts. Secondly, the standard marine predator algorithm is improved by using Bernoulli mapping, nonlinear attenuation weight function, and elite replacement strategy, and the model is solved by the improved algorithm. The results of the example optimization of a 21-node low-voltage distribution network show that the presented reactive power adjustment method can control the voltage point within a reasonable range and reduce the line loss rate. The improved marine predator algorithm has better global optimality finding and faster convergence than traditional intelligent algorithms.

An environmental education: how the education realignment polarized Congress on the environment

ABSTRACT As the international community attempts to unite to combat climate change, American party politics could hardly be more divided on this issue. This paper offers an additional explanation for how US congressional politics on environmental policy has polarized: the ongoing education realignment in American party politics. As the Democratic Party increasingly relies on college-educated voters and the opposite is true for the Republican Party, this can affect the parties’ positions on environmental policy based on public opinion research which finds a positive relationship between education and pro-environment attitudes. Using League of Conservation Voters legislative scorecards from 1983 to 2020, this paper finds the education realignment contributed to the removal of pro-environment Republicans and anti-environment Democrats in Congress in recent decades; and this primarily occurred through elite replacement rather than conversion.

NERS_HEAD: a new hybrid evolutionary algorithm for solving graph coloring problem

The graph coloring problem is an NP-hard problem. Currently, one of the most effective methods to solve this problem is a hybrid evolutionary algorithm. This paper proposes a hybrid evolutionary algorithm NERS_HEAD with a new elite replacement strategy. In NERS_HEAD, a method to detect the local optimal state is proposed so that the evolutionary process can jump out of the local optimal state by introducing diversity on time; a new elite structure and a replacement strategy are designed to increase the diversity of the evolutionary population so that the evolution process can not only converge quickly but also jump out of the local optimal state in time. The comparison experiments with current excellent graph coloring algorithms on 59 DIMACS benchmark instances show that NERS_HEAD can effectively improve the efficiency and success rate of solving graph coloring problems.

Challenging Civil Society Elites in Poland: The Dynamics and Strategies of Civil Society Actors

The shrinking of civil society—a problematic trend in a growing number of countries—often involves enacting legal measures to curtail the activity of civil society organizations and vilifying and/or harassing such organizations. Poland has been at the forefront of this trend since 2015. This article examines the mechanisms promoting elite replacement in Polish civil society, with a specific focus on the ways in which civil society actors have responded to these changes and the effectiveness of the state’s efforts to establish new hierarchies of power. The article discusses the complex relation between research on civil society and elite theory, and examines the anti-elitist discourses concerning Polish civil society and the strategies employed by the state to gain more control over the third sector. Next, the analytical section focuses on the ways in which civil society actors respond to state-sponsored elite change and examines three types of relations between the state and NGOs in contemporary Poland: (1) resistance, (2) assimilation, and (3) opportunistic synergy. In closing, the article shows ways in which analyses of the transformation of civil society in Poland and other countries can be enriched by drawing on elite theory.

A Novel Production Scheduling Approach Based on Improved Hybrid Genetic Algorithm

Due to the complexity of the production shop in discrete manufacturing industry, the traditional genetic algorithm (GA) cannot solve the production scheduling problem well. In order to enhance the GA-based method to solve the production scheduling problem effectively, the simulated annealing algorithm (SAA) is used to develop an improved hybrid genetic algorithm. Firstly, the crossover probability and mutation probability of the genetic operation are adjusted, and the elite replacement operation is adopted for simulated annealing operator. Then, a mutation method is used for the comparison and replacement of the genetic operations to obtain the optimal value of the current state. Lastly, the proposed hybrid genetic algorithm is compared with several scheduling algorithms, and the superiority and efficiency of the proposed method are verified in solving the production scheduling.

Evolutionary constrained optimization with hybrid constraint-handling technique

In constrained optimization evolutionary algorithms (COEAs), constraint-handling technique is used to balance the objective function and constraints, but how to achieve this balance is a very important problem. We found that the information of the population during the evolution process can reflect the current situation of the population, whether the population are inside the feasible region (feasible situation), or are near the boundary of the feasible region (semi-feasible situation), or far away from the feasible region (infeasible situation). Therefore, corresponding constraint-handling method are designed according to the information of each situation—Hybrid Constraint-handling Technique (HCT). The information of the population evolution process is used by HCT to maintain the objective function and constraints balance, and combines the evolutionary algorithm and HCT to propose ECO-HCT to solve COPs. Meanwhile, in infeasible situation, an elite replacement strategy is proposed to help the population accumulate experience. In addition, a criterion for judging that the population falls into the local optimum in the infeasible region and a simple restart mechanism are designed. They can help the population jump out of the local optimum in the infeasible region and effectively improve the algorithm’s ability to solve complex COPs. The 24 constraint test functions from IEEE CEC2006, the 28 constraint test functions from IEEE CEC2017, and three constrained engineering design problems are used to verify the effectiveness and efficiency of the proposed ECO-HCT. Experimental results show that ECO-HCT has very competitive performance compared with other advanced methods.

Retracted] Research on the Spread Path and Evolution Causes of Oral Language in the Digital Era

Visual orientation seems to indicate the decline of oral communication, but oral communication has its own living space under the new media ecology. Research has found that in the digital media era, voice communication is manifested as a single‐level feature that simulates current interaction and information communication. Although voice communication is a lie constructed by individuals, the interaction between the subject’s discourse and the actual field of interaction separate the emotional distance, but the situation is harmonious and inclusive. The following voice communication and new media technologies are still trustworthy. Aiming at multifactor evolutionary algorithm (MFEA), the most classical multifactor evolutionary algorithm in multitask computation, we theoretically analyze the inherent defects of MFEA in dealing with multitask optimization problems with different subfunction dimensions and propose an improved version of the multifactor evolutionary algorithm, called HD‐MFEA. In HD‐MFEA, we proposed heterodimensional selection crossover and adaptive elite replacement strategies, enabling HD‐MFEA to better carry out gene migration in the heterodimensional multitask environment. At the same time, we propose a benchmark test problem of multitask optimization with different dimensions, and HD‐MFEA is superior to MFEA and other improved algorithms in the test problem. Secondly, we extend the application scope of multitask evolutionary computation, and for the first time, the training problem of neural networks with different structures is equivalent to the multitask optimization problem with different dimensions. At the same time, according to the hierarchical characteristics of neural networks, a heterodimensional multifactor neural evolution algorithm HD‐MFEA neuro‐evolution is proposed to train multiple neural networks simultaneously. Through experiments on chaotic time series data sets, we find that HD‐MFEA neuro‐evolution algorithm is far superior to other evolutionary algorithms, and its convergence speed and accuracy are better than the gradient algorithm commonly used in neural network training.

Schooling the parties: the effect of the education realignment on LGBTQ+ party position taking in the US House of Representatives

ABSTRACT Much has been made of the ongoing partisan realignment of college-educated voters from the Republican to the Democratic Party, particularly the shift among college-educated whites. Less attention has been paid to how this realignment affects the nature of both the Republican and Democratic parties and the policies for which each advocate. This paper investigates the effect of this realignment on one policy area: LGBTQ+ issues, a policy area in which there is a significant difference in public opinion between college-educated and non-college-educated Americans. Using data on congressional activity on LGBTQ+ issues from 2005 to 2019, I test the effect of the education realignment in this policy area through both elite replacement and conversion. I find there is greater evidence for the realignment affecting party position taking through replacement, as a significant number of pro-LGBTQ+ Republicans and anti-LGBTQ+ Democrats were swept out of office in recent years. This furthers polarization on LGBTQ+ issues.

A New Job Shop Scheduling Method for Remanufacturing Systems Using Extended Artificial Bee Colony Algorithm

With the emergence of the remanufacturing industry, scheduling problems related to remanufacturing systems have drawn considerable interest from scholars. There are usually two execution modes of remanufacturing for reprocessing components, i.e., replacement mode and repair mode. However, few studies have focused on the job shop scheduling problem that considers the trade-off between the two execution modes. Thus, a new job shop scheduling method with job families (JSS-JF) is proposed, which can handle the selection of appropriate execution modes for reprocessing components with different damaged conditions. It decomposes the scheduling problem into three sub-problems: (1) execution mode selection; (2) replacement job assignment and sequencing; and (3) repair machine assignment and operation sequencing. The scheduling objective is to minimize the total completion time and total cost of job families. To solve the proposed JSS-JF model, an extended artificial bee colony algorithm with a new three-dimensional encoding scheme is presented to find a near-optimal solution of the proposed JSS-JF model. The crossover and mutation operators, local search, and elite replacement strategy are also integrated in the proposed algorithm. The experiments are conducted for verifying the practicality and effectiveness of the presented algorithm by comparing with six baseline algorithms.

Counter-Elite Populism and Civil Society in Poland: PiS’s Strategies of Elite Replacement

This article shows how Poland’s ruling party, Law and Justice (PiS), is attempting to apply its general strategy of “elite replacement” in a modified way to civil society. Since independent civil society organizations are not subject to arbitrary state control of appointments (unlike public institutions), this strategy has required a more complex dual approach of pressure and promotion. Organizations perceived as hostile to the party and its values have been subject to the withdrawal of state support and smear campaigns. By contrast, organizations that are politically or ideologically linked to the party have found support in the form of new public funds and other institutional assistance. This article examines the practical functioning and consequences of these processes through two main examples: (1) a state-sponsored campaign against one of Poland’s largest independent charity organizations, the Great Orchestra of Christmas Charity and (2) the funding of multiple right-wing NGOs friendly to PiS by the newly established National Freedom Institute. The article shows how PiS’s dual strategy in civil society reinforces its political narratives through support of the broader right-wing cultural narratives that underpin them. At the same time, it demonstrates how funding of friendly organizations directly strengthens party structures by fostering the development of new political and administrative cadres. By analysing PiS’s specific methods of pressure and promotion in the sphere of civil society, the article shows the intertwining of political and cultural narratives and goals within a right-wing populist framework.

A new environment-aware scheduling method for remanufacturing system with non-dedicated reprocessing lines using improved flower pollination algorithm

As the resource crisis and environmental pollution become increasingly prominent, remanufacturing is currently a popular research field for addressing these issues. However, scheduling for remanufacturing is more difficult than that for traditional manufacturing because the entire remanufacturing system (RMS) involves three cooperative subsystems: disassembly, reprocessing, and reassembly. Few studies have focused on the scheduling of the entire RMS and addressed the quality differences of defective components using non-dedicated reprocessing lines. Thus, this paper proposes a new environment-aware scheduling model for RMS, which considers not only three subsystems simultaneously, but also the non-dedicated reprocessing lines related to the recycled quality of defective components. The proposed model also integrates environmental factors by considering the carbon emissions of machines to take advantage of the environmental benefits in remanufacturing. To solve the proposed model, an improved flower pollination algorithm with new two-dimensional representation scheme is employed, which not only utilizes the self-adaptive parameter but also integrates path relinking technique, local search strategy, and elite replacement strategy. Experiments are performed to illustrate the effectiveness of the proposed algorithm for solving the remanufacturing scheduling problem by comparing it with six baseline algorithms.

Five Centuries of Inequality and Socioeconomic Transformation in the Barcelona Area, 1451-1880

Unequal distribution of wealth is a matter of growing concern in contemporary society, but it is also one with deep roots in the past. Several authors have traced the origins of this inequality by reconstructing historical series and collecting and harmonising data from sources and records with uneven territorial and temporal cover (Milanovic et al. (2011), Alfani (2015) Piketty (2014 and 2020)). Few places in the world have data series that make it possible to reconstruct the patterns of socioeconomic inequality by drawing on a single source. Barcelona, including its hinterland, is one of these places. The Barcelona Historical Marriage Database, which was created under the auspices of the Advanced Grant project Five Centuries of Marriages headed by Professor Anna Cabré, has made it possible to analyse, over a period of five centuries, the distribution of wealth by studying the taxes levied on marriages held in the Diocese from 1451 to 1880. This number of Perspectives Demogràfiques offers an account of the evolution of inequality from the ancien régime through to the consolidation of industrialisation, the concentration of wealth, and the composition and replacement of economic elites in the Barcelona area.

Replacement of Municipal Political Elite as a Tool for Seizing Power and Consolidating an Authoritarian Regime in Slovakia 1938–1940

The main aim of this article is to present a comparative historical analysis of the mechanisms for the replacement of the political elites after the collapse of interwar Czechoslovakia and the declaration of the Slovak State under the infl uence of Nazi Germany in the years 1938–1940 at the level of municipal self-government with regard to the onset of an authoritarian regime. The subjects of the research are two towns, Prešov and Nitra, which provide an opportunity to look for similarities and diff erences in the changes implemented in two socio-economically and demographically similar towns with diff erent political climates. The research is based on primary and secondary historical sources confronted mainly with the theories of V. Pareto, R. Michels and J. J. Linz. Historical developments in Slovakia in the years 1938–1940 and the process of the replacement of municipal elites correlates with the framework formulated in the sociological theories of Pareto and Michels. The process of the replacement of municipal elites contributed also to the gaining of characteristic elements of the authoritarian regime in the sense of the defi nition of J. J. Linz established in Slovakia by the Hlinka Slovak People’s Party.

An Evolutionary Algorithm for Many-Objective Optimization Based on Indicator and Vector-Angle Decomposition

The evolutionary algorithms for many-objective optimization based on reference-point decomposition are widely concerned since they generally maintain good performance on many optimization problems, however, most of these algorithms show insufficient versatility on optimization problems with various types of Pareto fronts. To address this issue, we propose an evolutionary algorithm for manyobjective optimization based on indicator and vector-angle decomposition, termed IVAD. In the proposed algorithm, the objective vectors of current population, as a set of reference vectors, are used to dynamically partition the whole objective space. And the max-min-vector-angle selection strategy, by calculating the vector angles between each pair of solutions, is constructed to select well-diversity solutions. Furthermore, to enhance the balance between convergence and diversity, the elite replacement, based on I <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">ε+</sub> indicator and vector angle, is proposed for each cluster that the selected individuals belong to. The proposed algorithm is compared with state-of-the-art many-objective evolutionary algorithms based on reference-point and vectorangle decomposition on three test suites with up to 15 objectives. Experimental results demonstrate that the proposed IVAD obtains more competitive performance on many-objective optimization problems with various types of Pareto fronts, and enhances the ability to balance convergence and diversity.

Hetero-Dimensional Multitask Neuroevolution for Chaotic Time Series Prediction

Chaotic time series prediction has important research and application value, and neural network-based prediction methods have problems such as low accuracy and difficulty in determining the number of nodes in the hidden layer. In recent years, as a representative of evolutionary multitask optimization algorithms(EMTO), multifactorial evolutionary algorithms (MFEA) have achieved excellent results in Multitask Optimization (MTO) problems, but it does not work well in solving hetero-dimensional multitask problem. We analyzed this phenomenon and proposed the concept of harmful transfer. Then to solve these problems, in this paper, we propose the hetero-dimensional multitask neuroevolution algorithms (HD-MFEA neuroevolution) for chaotic time series prediction. First, we propose hetero-dimensional assortative mating algorithm and self-adaption elite replacement algorithm, so that the hetero-dimensional multitask evolutionary algorithm (HD-MFEA) can overcome the problems caused by harmful transfer on hetero-dimensional multitask problem. Second, in order to adapt to the hierarchical characteristics of neural networks, we propose the neural level segmental coding strategy. Third, we consider the optimization of neural networks with different hidden layer nodes as hetero-dimensional multitask problem and use the HD-MFEA neuroevolution to solve this problem. We verify the effectiveness of the HD-MFEA on six hetero-dimensional multitask benchmark problems. The Mackey-Glass, Lorenz and Sunspot time series are used to demonstrate the performance of the HD-MFEA neuroevolution. Experimental results have showed that the HD-MFEA neuroevolution performs well in predicting the chaotic time series problems.

Binary-state line assignment optimization to maximize the reliability of an information network under time and budget constraints

Information networks are critical media for various applications of cloud computing and the Internet of Things. How to maintain the system reliability of an information network is an important issue for system supervisors. The system reliability is influenced by the capacities of the lines assigned to the edges that connect the vertices of the information network, where each line should operate to provide a certain capacity or fail. This study aims to maximize the system reliability of an information network by determining the optimal binary-state line assignment under an assignment budget constraint. In contrast to previous studies related to system reliability maximization, this study considers a time threshold in system reliability evaluation. In addition, the information network is regarded as a stochastic information network, as each edge may include several binary-state lines and provide multiple states. A method based on minimal paths and genetic algorithm (GA) with elite replacement is developed to evaluate the system reliability and search for the optimal solution. Several numerical experiments are conducted to show that the GA not only determines the exact solution but also exhibits higher computational efficiency than several well-known meta-heuristic algorithms.

A Genetic Algorithm with Best Combination Operator for the Traveling Salesman Problem

In this research, we propose a genetic algorithm with best combination operator (BC(x,y)O) for the traveling salesman problem. The idea of best combination operator is to find the best combination of some disjoint sub-solutions (also the reverse of sub-solutions) from some known solutions. We use BC(2,1)O together with a genetic algorithm. The proposed genetic algorithm uses the swap mutation operator and elitism replacement with filtration for faster computational time. We compare the performances of GA (genetic algorithm without BC(2,1)O), IABC(2,1)O (iterative approach of BC(2,1)O), and GABC(2,1)O (genetic algorithm with BC(2,1)O). We have tested GA, IABC(2,1)O, and GABC(2,1)O three times and pick the best solution on 50 problems from TSPLIB. From those 50 problems, the average of the accuracy from GA, IABC(2,1)O, and GABC(2,1)O are 65.12%, 94.21%, and 99.82% respectively.

Ocena elit politycznych w wystąpieniach w Sejmie Rzeczypospolitej Polskiej VIII kadencji

&lt;p&gt;Problematyka podjęta w niniejszym opracowaniu dotyczy sposobu, w jaki są postrzegane elity polityczne w niższej izbie polskiego parlamentu, przy czym materiał empiryczny (przedmiot badań) stanowią wystąpienia na forum Sejmu Rzeczypospolitej Polskiej VIII kadencji. Obraz elit politycznych jest zdecydowanie krytyczny, gdyż pozytywnie oceniano jedynie elity historyczne (od czasów Konstytucji 3 Maja po postawę elit w czasie II wojny światowej), z wyjątkiem „tak zwanej” elity komunistycznej. Wiele zarzutów przedstawiciele aktualnej elity rządzącej podnoszą w stosunku do elit Unii Europejskiej (tzw. elit brukselskich) oraz elit III Rzeczypospolitej Polskiej. Elita rządząca po 2015 r., uznając siebie (choć niezbyt chętnie) za elitę polityczną, wyjątkowo mocno podkreśla, iż nie jest rządem elit i nie działa w ich interesie, lecz dla dobra zwykłych obywateli. Dotychczasowa elita polityczna powinna zostać zastąpiona elitą narodową. Nie jest to jedynie zmiana pojęciowa, lecz podkreślenie, iż władzę powinni sprawować ludzie, którzy właściwie rozpoznają potrzeby narodu. Jest to reakcja na politykę prowadzoną przez rządy III Rzeczypospolitej Polskiej, kiedy – zdaniem obecnie sprawujących władzę – nie dbano o interesy ogółu społeczeństwa, a wyłącznie elit. Ze strony przedstawicieli elity opozycyjnej niewiele jest wypowiedzi dających odpór krytycznej ocenie elit politycznych, które rządziły po 1989 r. Wyjątkiem są głosy biorące w obronę elity sędziowskie jako autorytety, które jako jedyne mogą przeciwstawić się działaniom aktualnej władzy. Dostrzegany jest proces wymiany elit we wszystkich dziedzinach życia społecznego.&lt;/p&gt;

Does scientific eminence endure? Making sense of the most cited economists, psychologists and sociologists in textbooks (1970–2010)

This paper examines the concept of textbook eminence and asks whether this specific form of scholarly recognition is of a temporal rather than enduring nature. Based on an analysis of 30 leading textbooks in economics, psychology and economics from the 1970s and 2010s, it is established that less than a third of all eminent scholars remain across the period as the most cited authors. Therefore, the average “half-life” of textbook eminence is shorter than half a century. Textbook eminence, it seems, is associated first and foremost with ‘certified recognition,’ expressed through encyclopedia entries dedicated to individual scholars. In psychology, and partly in sociology, citation impact turns out to be a further significant correlate. In economics, however, textbook eminence is completely detached from peer recognition, as measured by the h-index. The identified short “half-life” of textbook eminence does not necessarily imply a replacement of older elites by younger researchers. In sociology, very few 20th century newcomers have yet attained textbook eminence.

A new fuzzy QoS-aware manufacture service composition method using extended flower pollination algorithm

With the increasing complexity of manufacturing tasks and the exponential growth of candidate services, manufacturing service composition has become considerably challenging in relation to the integration of service supply chains in fuzzy manufacturing environments. Quality of service (QoS), as a popular index, is widely used to evaluate the fitness of solutions to the manufacturing service composition (SMSC). In this study, we first establish a new fuzzy QoS-aware mathematical model that considers the preferences of manufacturing enterprises by assigning different sub-tasks with different weights to evaluate the global fuzzy QoS of the SMSCs. We then extend the flower pollination algorithm (FPA) to obtain an optimal SMSC more effectively by making the switch probability self-adaptive, improving the local search ability, and adding the strategy of elite replacement. Finally, we demonstrate that the proposed extended FPA is an effective and efficient algorithm for solving the manufacturing service composition problem with differently weighted sub-tasks in a fuzzy manufacturing environment. We do this by comparing it with other well-known metaheuristic algorithms such as basic FPA, genetic algorithm, cuckoo search algorithm, and particle swarm optimization.