Relevant bibliographies by topics / Win Maximization

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Book chapters
  4. Conference papers

Academic literature on the topic 'Win Maximization'

Author: Grafiati
Published: 4 June 2021
Last updated: 4 February 2022

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Journal articles on the topic "Win Maximization"

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Garcia-del-Barrio, Pedro, and Stefan Szymanski. "Goal! Profit Maximization Versus Win Maximization in Soccer." Review of Industrial Organization 34, no. 1 (2009): 45–68. http://dx.doi.org/10.1007/s11151-009-9203-6.

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Késenne, Stefan. "The Win Maximization Model Reconsidered." Journal of Sports Economics 7, no. 4 (2006): 416–27. http://dx.doi.org/10.1177/1527002505279347.

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Prinz, Aloys L. "Indirect Evolution and Aggregate-Taking Behavior in a Football League: Utility Maximization, Profit Maximization, and Success." Games 10, no. 2 (2019): 22. http://dx.doi.org/10.3390/g10020022.

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An evolutionary model of European football was applied to analyze a two-stage indirect evolution game in which teams choose their utility function in the first stage, and their optimal talent investments in the second stage. Given the second-stage optimal aggregate-taking strategy (ATS) of talent investment, it was shown that teams may choose a mix of profit or win maximization as their objective, where the former is of considerably higher relevance with linear weights for profits, and is more successful in the utility function. With linear weights for profit and win maximization, maximizing profits is the only evolutionarily stable strategy (ESS) of teams. The results change if quadratic weights for profits and wins are employed. With increasing talent productivity, win maximization dominates in the static and in the dynamic versions of the model. As a consequence, it is an open question whether the commercialization of football (and other sports) leagues will lead to more profit or win maximization.
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D’Souza, Márcia Figueredo, Gerlando Augusto Sampaio Franco de Lima, Daniel N. Jones, and Jessica R. Carré. "Do I win, does the company win, or do we both win? Moderate traits of the Dark Triad and profit maximization." Revista Contabilidade & Finanças 30, no. 79 (2019): 123–38. http://dx.doi.org/10.1590/1808-057x201806020.

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ABSTRACT This article analyzes the relationship between the maximization of personal and company gains and the moderate traits of the Dark Triad. The relevance of choosing this topic lies in investigating the attitude of executives who exhibit characteristics of a moderate intensity between the strong and weak traits. It is proven that the vision and charisma of narcissistic individuals, the strategy and tactics of Machiavellian individuals, and the creativity and good strategic thinking of psychopathic individuals are differentiating characteristics that enhance successful and integrative leadership and that are far from the more accentuated and opportunistic attitudes related to the strong traits, whose practices involve dishonest actions for personal gain. This evidence creates the possibility for strengthening the research in the accounting area, especially on the behavioral approach, in order to promote its interface with psychology and clarify how personality, values, and experiences influence managers’ choices when conducting business and how workers and companies are impacted by these decisions. The study is empirical-theoretical and involves 263 managers, adopting a survey as its data collection strategy and applying a self-reporting type questionnaire. The data analysis approaches included descriptive statistics, correlations, tests of means, and logistic regressions. In this study, managers with moderate psychopathic traits showed a lower tendency to maximize profit by manipulating results. An opposite tendency was revealed for those with moderate Machiavellian traits. The combined effect of the three Dark Triad traits was significant and positive, revealing opportunistic profit maximization. These findings contribute to future studies that aim to systematically analyze moderate levels of the triad and corroborate the findings that have revealed the common characteristics of manipulation, callousness, and dishonesty when investigating the interactive effect between the traits in question.
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Terrien, Mickael, Nicolas Scelles, Stephen Morrow, Lionel Maltese, and Christophe Durand. "The win/profit maximization debate: strategic adaptation as the answer?" Sport, Business and Management: An International Journal 7, no. 2 (2017): 121–40. http://dx.doi.org/10.1108/sbm-10-2016-0064.

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Purpose The purpose of this paper is twofold. First, to highlight the heterogeneity of the organizational aims within the professional football teams in Ligue 1. Second, to understand why some teams swing from a win orientation towards a soft budget constraint from year to year, and vice versa. Design/methodology/approach Financial data from annual reports for the period 2005/2015 was collected for the 35 Ligue 1 clubs. To define the degree of compliance with the intended strategy for those clubs, an efficiency analysis was conducted thanks to the data envelopment analysis method. This measure of performance was supplemented with the identification of productivity and demand shocks to identify whether clubs suffered from such shock or changed their strategy. It enables to precise the nature of the evolution in the utility function, with regards to the gap between expectation and actual performance. Findings The paper suggests that a team can switch from one orientation to another from year to year due to the uncertain nature of the sports industry. The club director’s utility function could also be maximized under inter temporal budget function in order to adjust the weight between win and profit according to the opportunities in the environment. Originality/value The paper sheds new light on the win/profit maximization. The theoretical model provides an assessment of the weight between win and profit in Ligue 1 and then identifies a new explanation for persistent losses in the sports industry.
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Freeman, Olivia E., and Hisham Zerriffi. "Carbon credits for cookstoves: Trade-offs in climate and health benefits." Forestry Chronicle 88, no. 05 (2012): 600–608. http://dx.doi.org/10.5558/tfc2012-112.

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Cookstove projects have long been considered “win–win” development projects based on the multitude of benefits they can create. Carbon credits provide a new financing mechanism to fund such cookstove projects, but have been criticized as not always successfully meeting sustainable development goals. By drawing on previous literature this article critically looks at trade-offs between the maximization of climate and health benefits of cookstove projects in the context of carbon credits. It finds that carbon credits inherently account for climate benefits, but not for health. Therefore, clear objectives of cookstove interventions need to be defined prior to project implementation to insure the maximization of benefits in projects’ priority areas.
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Hwang, Yu, Issac Sim, Young Sun, Heung-Jae Lee, and Jin Kim. "Game-Theory Modeling for Social Welfare Maximization in Smart Grids." Energies 11, no. 9 (2018): 2315. http://dx.doi.org/10.3390/en11092315.

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In this paper, we study the Stackelberg game-based evolutionary game with two players, generators and energy users (EUs), for monetary profit maximization in real-time price (RTP) demand response (DR) systems. We propose two energy strategies, generator’s best-pricing and power-generation strategy and demand’s best electricity-usage strategy, which maximize the profit of generators and EUs, respectively, rather than maximizing the conventional unified profit of the generator and EUs. As a win–win strategy to reach the social-welfare maximization, the generators acquire the optimal power consumption calculated by the EUs, and the EUs obtain the optimal electricity price calculated by the generators to update their own energy parameters to achieve profit maximization over time, whenever the generators and the EUs execute their energy strategy in the proposed Stackelberg game structure. In the problem formulation, we newly formulate a generator profit function containing the additional parameter of the electricity usage of EUs to reflect the influence by the parameter. The simulation results show that the proposed energy strategies can effectively improve the profit of the generators to 45% compared to the beseline scheme, and reduce the electricity charge of the EUs by 15.6% on average. Furthermore, we confirmed the proposed algorithm can contribute to stabilization of power generation and peak-to-average ratio (PAR) reduction, which is one of the goals of DR.
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Ehrlich, Justin, Shane Sanders, and Christopher J. Boudreaux. "The relative wages of offense and defense in the NBA: a setting for win-maximization arbitrage?" Journal of Quantitative Analysis in Sports 15, no. 3 (2019): 213–24. http://dx.doi.org/10.1515/jqas-2018-0095.

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Abstract In basketball, a point scored on offense carries a nearly identical on-court (win) value as a point denied on defense (e.g. within the Pythagorean expected wins model). Both outcomes bear the same score margin implication. As such, a win-maximizing team is expected to value the two outcomes equally. We ask whether the salaries of NBA players reveal such an equality among NBA teams. If not, a win-maximizing team would enjoy a disequilibrium arbitrage opportunity, whereby the team could improve, in expectation, even while reducing roster payroll. We considered the 322 National Basketball Association (NBA) players during the 2016–2017 season who were on a full-season contract for which the salary was not stipulated under the NBA Collective Bargaining Agreement. We estimated the implied marginal wage of an additional point created on offense (denied on defense) per 100 possessions. Namely, we constructed a set of fixed effects, ordinary least squares regression models that specify a player’s pre-assigned 2016–2017 player salary as a function of primary team fixed effects, offensive adjusted plus minus, defensive adjusted plus minus, position-of-play, and control variables such as age. We conclude that a win-maximizing NBA team currently faces a substantial arbitrage opportunity. Namely, one unit of offense carries the same estimated implicit salary as approximately two and a half to four units of defense. We also find moderate between-team variation in adjusted plus minus return on payroll allocations.
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Goff, Brian, and Stephen L. Locke. "Revisiting Romer: Digging Deeper Into Influences on NFL Managerial Decisions." Journal of Sports Economics 20, no. 5 (2018): 671–89. http://dx.doi.org/10.1177/1527002518798686.

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Using Romer’s framework as the starting point, we examine the decisions by National Football League (NFL) coaches to “go for it” on fourth down with an expanded sample drawn from 12 years (2002-2013) of NFL play-by-play data. Our expanded results generally confirm Romer’s finding of divergence from expected point maximization or win maximization. However, unlike Romer, by estimating forecast errors for points and wins and related risk premia along with logistic regression estimates of the influences on fourth down decisions, we find strong indications that risk aversion rather than incorrect information processing likely accounts for a substantial part of the divergence.
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Osokin, N. A. "Win vs. Profit maximization: optimal strategy for managing organizational performance of russian football clubs." Strategic decisions and risk management, no. 2 (July 15, 2018): 86–91. http://dx.doi.org/10.17747/2078-8886-2018-2-86-91.

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The cause-effect relationships between performance dimensions were assessed using a multivariate linear regression. The author analyzes the strategic behavior of Russian football clubs using the profit/win maximization classification. The causality tests allowed the author to form a conceptual model of the main performance dimensions of professional football clubs in Russia. The results help better understand the managerial pitfalls in Russian club football. The article contributes to the literature on organizational performance of professional football clubs by focusing on the Russian context, which has not been done previously. The findings of the paper confront the managerial fallacies of Russian club football and broaden the understanding of club football management practices in general.
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Dissertations / Theses on the topic "Win Maximization"

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Bhargava, Tanvi. "Financial Performance of Football Teams: Effects of Win Maximization, Performance and Transfer Spending on Stock Prices." Scholarship @ Claremont, 2017. http://scholarship.claremont.edu/cmc_theses/1565.

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The present paper explores the effects of championships won and financial stability of the clubs on share price returns for publicly traded football clubs in Europe. The study uses samples from 2012-2017 of 14 publicly traded clubs on different exchanges such as Borsa Italiana, London Stock Exchange, New York Stock Exchange, Germany Stock Exchange, Paris CAC Index, Borsa Lisbon, Copenhagen Stock Exchange as well as the Turkish Stock Exchange. The initial analysis assesses share price returns’ links with team performance and team financial variables as well as two indices: STOXX 600 Market Index and the STOXX Football Index. Further analysis includes looking at revenues and the different variables that affect returns to see the correlation and understand profitability vs win maximization due to the effect of sugar daddy owners. There appears to be a negative and significant correlation between profit margin and returns, and I also conduct event studies for the biggest transfers of the clubs and conclude that in the short term, there is a significant effect on share prices when transfers occur.
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Pilavci, Burak. "On-pitch success in UEFA Champions League : an empirical analysis of economic, demographic and traditional factors." Thesis, Högskolan i Jönköping, Internationella Handelshögskolan, 2011. http://urn.kb.se/resolve?urn=urn:nbn:se:hj:diva-22568.

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This paper’s aim is to discover the impact of economical, demographic and traditional determinants on clubs’ on-pitch success in UEFA Champions League. Generally it is assumed by people that financially strong clubs tend to win on the pitch most of the time. Is it really true? Is it always the same wealthy teams which win in the end? Football is a type of entertainment and people would like to see games with uncertain outcomes and a balanced competitiveness between two sides. In this way they can enjoy this entertainment. In that case, how uncertain is the outcome and how balanced is the competition in UEFA Champions League? In order to answer all these questions a multiple regression analysis is built including economic, demographic and traditional variables both at club and country level. These mentioned explanatory variables are GDP per capita of the home country, population of the host city, total market value of the team’s players, capacity of the stadium, country’s participation in international tournaments, club’s age, rank of the next best team from the same country and country’s hosting an international tournament. It turned out that financially advantageous clubs which have stadiums with larger capacities and located in more populated cities have more chances of winning than the others. Then again, it is observed that countries’ football tradition and dedication does not have a significant impact on clubs’ on-pitch success in UEFA Champions League.
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Wang, Yang. "Modified simultaneous perturbation stochastic approximation method for power capture maximization of wind turbines." Thesis, Kansas State University, 2013. http://hdl.handle.net/2097/16296.

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Master of Science<br>Department of Mechanical and Nuclear Engineering<br>Warren N. White<br>As traditional resources are becoming scarce, renewable energy is a recent topic receiving greater concern. Among the renewable energies, wind power is a very popular type of energy extracted from wind which is readily available in the environment. The use of wind power all over the world is receiving increased attention. Horizontal axis wind turbines are the most popular equipment for extracting power form the wind. One of the problems of using wind turbines is how to maximize the wind power capture. In this paper, a method for maximizing the rotor power coefficient of a wind turbine is proposed. Simultaneous Perturbation Stochastic Approximation (SPSA) is an efficient way for extremum seeking. It is different from the classical gradient based extremum seeking algorithms. For maximizing the rotor power coefficient, it only needs two objective function measurements to take a step toward the next extremum approximation. The one measurement SPSA is a modification of SPSA method developed in this work. Instead of using measurements of two positions occurring at random directions away from the current position, it uses the measurement of one position in a random direction and the measurement of the current position to estimate the gradient. Usually, the rotor power coefficient is not easily measurable. For speed regulation, a nonlinear robust speed controller is used in this work. The controller produces an estimate of the aerodynamic torque of wind turbine. The quality of this estimate improves with time. From that, a good estimate of power coefficient can be obtained. Simulations in MATLAB are executed with a model of a wind turbine based on its dynamic equations. From simulations, it can be seen that the one measurement SPSA method works very well for the wind turbine. It changes the tip speed ratio and blade pitch simultaneously, and the power coefficient reaches its maximum value quickly in a reliable manner. The power capture optimization is then implemented in FAST, a turbine simulation model created by NREL which is used to test the 5MW NREL reference turbine. From the results, it is evident that the wind turbine reaches the maximum power coefficient rapidly.
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Hawkins, Tony (Greg Anthony). "Maximization of power capture in wind turbines using robust estimation and Lyapunov extremum seeking control." Thesis, Kansas State University, 2010. http://hdl.handle.net/2097/4643.

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Master of Science<br>Department of Mechanical and Nuclear Engineering<br>Guoqiang Hu<br>Warren N. White<br>In recent years, the concern has risen to establish clean sources for electric power generation. In 2009, Kansas established an RPS (Renewable Portfolio Standard) mandating utilities acquire 20% of their electricity from renewable energy by 2020 [32]. One of the most prominent renewable energy sources is wind energy. Utility companies now are investing more in wind capture systems to comply with this mandate. This increase in the manufacture of wind turbines has caused researchers to investigate methods to improve the efficiency of captured wind energy and where improvements can be made. This thesis takes a control theory approach to maximizing the power capture of a wind turbine using the concepts of robust estimation, nonlinear control, and Lyapunov-based maximization. A two step control approach to optimize the power capture of a wind turbine is proposed. First, a robust controller is used to estimate unknown aerodynamic properties and regulate the wind turbine tip-speed ratio as it tracks a desired trajectory. Once the tip-speed ratio is regulated within a given tolerance, a Lyapunov-based control approach is developed to provide the robust controller with a desired trajectory to track. This is done by estimating the unknown coefficient of performance of the wind turbine. A discrete update law is then developed to alter the tip-speed ratio and the blade pitch of the wind turbine so that the coefficient of performance is maximized. A simulation is provided of this control strategy and tested under time varying wind conditions and measurement noise in order to demonstrate the controller’s performance. The system simulated is intended to emulate a commercial wind turbine operating in a realistic environment. A detailed discussion of the simulation model, control scheme, and results will be provided to supplement the theoretical controller development, as well as future work for this control application.
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Siniscalchi, Minna Sara. "Advanced wind farm control strategies for enhancing grid support." Doctoral thesis, TDX (Tesis Doctorals en Xarxa), 2019. http://hdl.handle.net/10803/669244.

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Nowadays, there is rising concern among Transmission System Operators about the declining of system inertia due to the increasing penetration of wind energy, and other renewable energy systems, and the retirements of conventional power plants. On the other hand, by properly operating wind farms, wind generation may be capable of enhancing grid stability and ensuring continued security of power supply. In this doctoral thesis, new control approaches for designing wind farm optimization-based control strategies are proposed to improve the participation of wind farms in grid support, specially in primary frequency support.<br>Hoy en día, existe una significativa preocupación entre los Operadores de Sistemas de Transmisión sobre la cresciente penetración de le energía eólica y la tendiente eliminación de las centrales eléctricas convencionales que implica la disminución de la inercia del sistema eléctrico. Operando adecuadamente los parques eólicos, la generación eólica puede mejorar la estabilidad de la red eléctrica y garantizar la seguridad y un continuo suministro de energía. Esta tesis doctoral propone nuevas estrategias para diseñar controladores basados en optimización dinámica para parques eólicos y mejorar la participación de los parques eólicos en el soporte de la red eléctrica. En primer lugar, esta tesis doctoral presenta los enfoques clásicos para el control de parques y turbinas eólicas y cómo los conceptos de control existentes pueden ser explotados para hacer frente a los nuevos desafíos que se esperan de los parques eólicos. Esta tesis doctoral asigna un interés especial a cómo formular la función objetivo de que la reserva de potencia sea maximizada, para ayudar por el suporte de frequencia, y al mismo tiempo seguir la potencia demandada por la red. Sin embargo, el impacto de la estela de viento generada por una turbina sobre otras turbinas necesita ser minimizado para mejorar la reserva de potencia. Por lo tanto, a lo largo de esta tesis se proponen estrategias de control centralizado para parques eólicos enfocadas en distribuir óptimamente la energía entre las turbinas para que el impacto negativo de la estela en la reserva de potencia total se reduzca. Se discuten dos técnicas de control para proporcionar los objetivos de control mencionados anteriormente. Un algoritmo de control óptimo para encontrar la mejor distribución de potencia entre las turbinas en el parque mientras se resuelve un problema iterativo de programación lineal. En segundo lugar, se utiliza la técnica de control predictivo basada en modelo para resolver un problema de control multi-objetivo que también podría incluir, junto con la maximización de reserva de potencia, otros objetivos de control, tales como la minimización de las perdidas eléctricas en los cables de la red de interconexión entre turbinas y un controlador/supervisor. Además, la investigación realizada resalta la capacidad de las estrategias de control propuestas en esta tesis para proporcionar mayor reserva de potencia respecto a los conceptos comúnmente usados para distribuir la potencia total del parque eólico. La idea principal detrás del diseño de una estrategia de control de parques eólico es de encontrar una solución óptima dentro de un cálculo computacional relativamente bajo. Aunque los controladores centralizados propuestos en esta tesis reaccionan rápidamente a los cambios en la potencia de referencia enviada desde el controlador, algunos problemas pueden ocurrir cuando se consideran parques eólicos de gran escala debido a los retrasos existentes por el viento entre turbinas. Bajo estas circunstancias, la producción de energía de cada turbina está altamente acoplada con la propagación de la estela y, por ende, con las condiciones de funcionamiento de las otras turbinas. Esta tesis doctoral propone un esquema de control de parques eólicos no centralizados basado en una estrategia de partición para dividir el parque eólico en sub-conjuntos independientes de turbinas. Con la estrategia de control propuesta, el tiempo de cálculo se reduce adecuadamente en comparación con la estrategia de control centralizado mientras que el rendimiento en la distribución óptima de potencia es ligeramente afectado. El rendimiento de todas las estrategias de control propuestas en esta tesis se prueba con un simulador de parque eólico que modela el comportamiento dinámico del efecto de estela mediante el uso de un conocido y consolidado modelo dinámico de estela y, para un análisis más realista, algunas simulaciones se realizan con software avanzado basado en la técnica de Large Eddy Simulation.
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Kinjo, Fuminao. "Maximization of energy capture of passive, variable-speed wind-turbine." Thesis, 2003. http://hdl.handle.net/1957/32375.

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This thesis presents and examines the concept that the output of a wound-rotor induction generator (WRIG) can be limited by means of linking to external impedances for wind-turbine generating system application. An 80kW-WRIG is simulated as a model to examine the control of the output power vs. speed characteristic. Model of WRIG derived from per phase equivalent circuit is organized, then it is estimated how much external impedances affect the characteristic of output power for it to approach to a typical wind-turbine curve. Practical tests are performed using 80kW-WRIG in testing lab to validate the simulation data. In addition, a smaller WRIG, connected on same shaft as 80kW-WRIG, is designed to extend the range of wind speed. Also external impedances with smaller WRIG are chosen to extract optimum power from wind-turbine. Finally, passively controlled tandem WRIGs are shown to have the capability to optimize wind-turbine energy extraction when controlled entirely by external impedances.<br>Graduation date: 2003
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Zubo, Rana H. A., Geev Mokryani, and Raed A. Abd-Alhameed. "Optimal operation of distribution networks with high penetration of wind and solar power within a joint active and reactive distribution market environment." 2018. http://hdl.handle.net/10454/14922.

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Yes<br>In this paper, a stochastic approach for the operation of active distribution networks within a joint active and reactive distribution market environment is proposed. The method maximizes the social welfare using market based active and reactive optimal power flow (OPF) subject to network constraints with integration of demand response (DR). Scenario-Tree technique is employed to model the uncertainties associated with solar irradiance, wind speed and load demands. It further investigates the impact of solar and wind power penetration on the active and reactive distribution locational prices (D-LMPs) within the distribution market environment. A mixed-integer linear programming (MILP) is used to recast the proposed model, which is solvable using efficient off-the shelf branch-and cut solvers. The 16-bus UK generic distribution system is demonstrated in this work to evaluate the effectiveness of the proposed method. Results show that DR integration leads to increase in the social welfare and total dispatched active and reactive power and consequently decrease in active and reactive D-LMPs.<br>Ministry of Higher Education and Scientific Research of Iraq
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Zubo, R. H. A., Geev Mokryani, and Raed A. Abd-Alhameed. "Optimal operation of distribution networks with high penetration of wind and solar power within a joint active and reactive distribution market environment." 2002. http://hdl.handle.net/10454/14922.

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Yes<br>In this paper, a stochastic approach for the operation of active distribution networks within a joint active and reactive distribution market environment is proposed. The method maximizes the social welfare using market based active and reactive optimal power flow (OPF) subject to network constraints with integration of demand response (DR). Scenario-Tree technique is employed to model the uncertainties associated with solar irradiance, wind speed and load demands. It further investigates the impact of solar and wind power penetration on the active and reactive distribution locational prices (D-LMPs) within the distribution market environment. A mixed-integer linear programming (MILP) is used to recast the proposed model, which is solvable using efficient off-the shelf branch-and cut solvers. The 16-bus UK generic distribution system is demonstrated in this work to evaluate the effectiveness of the proposed method. Results show that DR integration leads to increase in the social welfare and total dispatched active and reactive power and consequently decrease in active and reactive D-LMPs.<br>Ministry of Higher Education and Scientific Research of Iraq
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Book chapters on the topic "Win Maximization"

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Manimegalai, R., S. Visalakshi, and Lucina Joseph. "PSO Based Social Welfare Maximization of Wind Thermal Coordinated System in a Deregulated Power Market." In Lecture Notes in Electrical Engineering. Springer India, 2014. http://dx.doi.org/10.1007/978-81-322-2119-7_80.

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Abdelmjid, Baddou, El Kari Abdeljalil, Ayad Hassan, and Mjahed Mostafa. "Intelligent Methods for the Maximization of the Energy of Wind Systems with Synchronous Generators Permanent Magnet." In Lecture Notes in Electrical Engineering. Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-13-1405-6_67.

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Gana, Ovidiu, Octavian Prostean, and Marius Babescu. "Maximization of the Energy and Flattening of Fluctuations for the Power Generated into the Network at a Wind Driven Electro Energetic System." In Soft Computing Applications. Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-33941-7_21.

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Mokhtari, Mohammed, Smail Zouggar, Nacer K. M’sirdi, and Mohamed Larbi Elhafyani. "Contribution to Power Maximization of an Asynchronous Wind Electric Water Pumping System Using Single Input Fuzzy Logic Controller and Modified Enhanced Perturb and Observe." In Advances in Smart Technologies Applications and Case Studies. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-53187-4_37.

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Shugart, Matthew S., Matthew E. Bergman, Cory L. Struthers, Ellis S. Krauss, and Robert J. Pekkanen. "New Zealand." In Party Personnel Strategies. Oxford University Press, 2021. http://dx.doi.org/10.1093/oso/9780192897053.003.0010.

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This chapter focuses on the impact of electoral reform in New Zealand, which changed from first-past-the post (FPTP) to mixed-member proportional (MMP). The chapter analyzes the National and Labour parties under both electoral systems. As expected, the expertise model becomes more important to parties’ allocation of legislators to House of Representatives committees after the electoral reform to MMP, due to the move to a system in which votes cast anywhere count toward seat maximization. Parties also change how they assign members under the electoral–constituency model, as the system moves from one in which winning districts is the exclusive way in which a party maximizes seats to one in which legislators representing districts may be leveraged to help the party win more votes from the party list. Both parties show strong issue ownership tendencies before and after electoral reform.
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Jones, Roselin. "Lifetime Maximization of Target-Covered WSN Using Computational Swarm Intelligence." In Advances in Wireless Technologies and Telecommunication. IGI Global, 2019. http://dx.doi.org/10.4018/978-1-5225-7335-7.ch018.

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In target-covered WSN, all critical points (CPs) are to be monitored effectively. Even a single node failure may cause coverage hole reducing the lifetime of the network. The sensor has non-rechargeable battery, and hence, energy supervision is inevitable. To maximize the lifetime of the WSN with guaranteed coverage and effective battery utilization, the activities of the sensors are to be scheduled and also the sensors may be repositioned towards the critical points. This chapter proposes an energy-efficient coverage-based artificial bee colony optimization (EEC-ABC) approach that exploits the intelligent foraging behavior of honeybee swarms to solve EEC problem to maximize the lifetime of the WSN. It also adheres to quality of service metrics such as coverage, residual energy, and lifetime. Similarly, energy-balanced dynamic deployment (EB-DD) optimization approach is proposed to heal the coverage hole to maximize the lifetime of the WSN. It positions the self-deployable mobile sensors towards the CPs to balance their energy density and thus enhances the lifetime of the network.
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S, Ramprakash, Vijayakumari B, and Subathra P. "Minimizing Delay and Maximizing Network Lifetime by Power-Aware Energy Efficient Routing [PAEER] Mechanism in Wireless Sensor Networks." In Intelligent Systems and Computer Technology. IOS Press, 2020. http://dx.doi.org/10.3233/apc200177.

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We propose an efficient routing mechanism called PAEER (Power-Aware Energy Efficient Routing) for meeting Network Lifetime Maximization and energy efficiency in the Wireless Sensor Networks(WSN). The different contributions of the PAEER approach are following (a) Multisink node approach which can lead to increase the nodes network lifetime and event detection mechanism that meets reliability requirement of the WSN (b) Using PAEER mechanism sends the data to sink node by covering multi-path routes to aggregate the nodes data. Thus energy consumption of the WSN can be reduced maximum level therefore network lifetime increased. This can be proved both theoretical and experiment solutions can be better when compared to other solutions. By using Network Simulator-3 (NS-3) testbed the results show the better results for the all Quality of Service parameters (QoS) like Throughput, Network Lifetime, Power Consumption, etc.
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Mittal, Prateek, and Kishalay Mitra. "Decomposition-Based Multi-Objective Optimization of Energy Noise Trade-Off in a Wind Farm." In Handbook of Research on Emergent Applications of Optimization Algorithms. IGI Global, 2018. http://dx.doi.org/10.4018/978-1-5225-2990-3.ch008.

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A multi-objective optimization case study of maximization and minimization of energy generation and noise propagation is considered here. A novel hybrid methodology, as a combination of probabilistic variable decomposed multi-objective evolutionary algorithm (VdRBNSGA-II) and the newly developed deterministic gradient based Pareto frontier construction approach (nD-NNC), has been proposed to determine the optimum layout of turbines (numbers and locations) inside a wind farm. In contrast to previous case studies, the proposed approach is able to yield the alternative energy-noise solutions along with the additional information on corresponding turbine layouts (numbers and locations) on a single Pareto front. As a result, it provides a decision maker with an ample of choices to choose from different competing solutions based on the existing standards and guidelines.
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Babescu, Marius, Constantin Bota, and Bogdan Caruntu. "Maximization of the Energy of a Wind System with a Synchronous Generator." In DAAAM Proceedings. DAAAM International Vienna, 2011. http://dx.doi.org/10.2507/22nd.daaam.proceedings.379.

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Corradini, M. L., G. Ippoliti, and G. Orlando. "Efficiency maximization of wind turbines using data-driven Model-Free Adaptive Control." In Renewable Energy Systems. Elsevier, 2021. http://dx.doi.org/10.1016/b978-0-12-820004-9.00007-3.

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Conference papers on the topic "Win Maximization"

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Ali, Khurshed, Chih-Yu Wang, and Yi-Shin Chen. "Boosting Reinforcement Learning in Competitive Influence Maximization with Transfer Learning." In 2018 IEEE/WIC/ACM International Conference on Web Intelligence (WI). IEEE, 2018. http://dx.doi.org/10.1109/wi.2018.00-62.

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Alhamed, Khalid, Markus Zanker, Shakre Elmane, and Marius Silaghi. "P2P Meta-Recommenders: Aggregated Diversity Maximization as a Bulwark against Attacks on Reviewers." In 2016 IEEE/WIC/ACM International Conference on Web Intelligence (WI). IEEE, 2016. http://dx.doi.org/10.1109/wi.2016.0038.

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Arab, Mohsen, and Mohsen Afsharchi. "A Modularity Maximization Algorithm for Community Detection in Social Networks with Low Time Complexity." In 2012 IEEE/WIC/ACM International Joint Conferences on Web Intelligence (WI) and Intelligent Agent Technologies (IAT). IEEE, 2012. http://dx.doi.org/10.1109/wi-iat.2012.97.

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Quan, Ning, and Harrison Kim. "A Mixed Integer Linear Programming Formulation for Unrestricted Wind Farm Layout Optimization." In ASME 2015 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2015. http://dx.doi.org/10.1115/detc2015-46876.

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This paper proposes a mixed integer linear programming formulation of the unrestricted wind farm layout optimization problem. The formulation is achieved in part by changing the objective from power generation maximization to the maximization of the smallest penalized downstream distance between any pair of turbines, where downstream distance is defined as the distance between any pair of turbines with overlapping wake cones. The proposed formulation also linearizes other non-linear characteristics of the unrestricted layout optimization problem such as proximity constraints and wake-cone membership. The main advantage of the proposed approach is that an optimal solution to the proposed formulation is guaranteed to be globally optimal. This is in contrast to previous approaches with non-linear formulations that do not come with such guarantees.
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Guo, Yi, Mario Rotea, and Tyler Summers. "Stochastic Dynamic Programming for Wind Farm Power Maximization." In 2020 American Control Conference (ACC). IEEE, 2020. http://dx.doi.org/10.23919/acc45564.2020.9148006.

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Srinidhi, N. N., G. P. Sunitha, Nagarjun E, Shreyas J, and S. M. Dilip Kumar. "Lifetime Maximization of IoT Network by Optimizing Routing Energy." In 2019 IEEE International WIE Conference on Electrical and Computer Engineering (WIECON-ECE). IEEE, 2019. http://dx.doi.org/10.1109/wiecon-ece48653.2019.9019967.

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Kwong, Wing Yin, Peter Y. Zhang, David Romero, Joaquin Moran, Michael Morgenroth, and Cristina Amon. "Wind Farm Layout Optimization Considering Energy Generation and Noise Propagation." In ASME 2012 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2012. http://dx.doi.org/10.1115/detc2012-71478.

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Wind farm design deals with the optimal placement of turbines in a wind farm. Past studies have focused on energy-maximization, cost-minimization or revenue-maximization objectives. As land is more extensively exploited for onshore wind farms, wind farms are more likely to be in close proximity with human dwellings. Therefore governments, developers, and landowners have to be aware of wind farms’ environmental impacts. After considering land constraints due to environmental features, noise generation remains the main environmental/health concern for wind farm design. Therefore, noise generation is sometimes included in optimization models as a constraint. Here we present continuous-location models for layout optimization that take noise and energy as objective functions, in order to fully characterize the design and performance spaces of the optimal wind farm layout problem. Based on Jensen’s wake model and ISO-9613-2 noise calculations, we used single- and multi-objective genetic algorithms (NSGA-II) to solve the optimization problem. Preliminary results from the bi-objective optimization model illustrate the trade-off between energy generation and noise production by identifying several key parts of Pareto frontiers. In addition, comparison of single-objective noise and energy optimization models show that the turbine layouts and the inter-turbine distance distributions are different when considering these objectives individually. The relevance of these results for wind farm layout designers is explored.
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Kumar, Devesh, and Mario Rotea. "Log-power PIESC for wind turbine power maximization below-rated wind conditions." In AIAA Scitech 2021 Forum. American Institute of Aeronautics and Astronautics, 2021. http://dx.doi.org/10.2514/6.2021-1288.

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Yongrui Chen, Yang Yang, and Weidong Yi. "A cooperative routing algorithm for lifetime maximization in wireless sensor networks." In IET International Conference on Wireless Sensor Network 2010 (IET-WSN 2010). IET, 2010. http://dx.doi.org/10.1049/cp.2010.1047.

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Marek, Jaroslav, and Jana Heckenbergerova. "Expectation-maximization algorithm for evaluation of wind direction characteristics." In 2015 IEEE 15th International Conference on Environment and Electrical Engineering (EEEIC). IEEE, 2015. http://dx.doi.org/10.1109/eeeic.2015.7165433.

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