Relevant bibliographies by topics / Penalty function

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  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Penalty function'

Author: Grafiati
Published: 4 June 2021
Last updated: 3 February 2022

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Journal articles on the topic "Penalty function"

1

Xu, Xinsheng, Zhiqing Meng, Jianwu Sun, and Rui Shen. "A penalty function method based on smoothing lower order penalty function." Journal of Computational and Applied Mathematics 235, no. 14 (May 2011): 4047–58. http://dx.doi.org/10.1016/j.cam.2011.02.031.

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Nguyen, Binh Thanh, Yanqin Bai, Xin Yan, and Touna Yang. "Perturbed smoothing approach to the lower order exact penalty functions for nonlinear inequality constrained optimization." Tamkang Journal of Mathematics 50, no. 1 (March 30, 2018): 37–60. http://dx.doi.org/10.5556/j.tkjm.50.2019.2625.

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In this paper, we propose two new smoothing approximation to the lower order exact penalty functions for nonlinear optimization problems with inequality constraints. Error estimations between smoothed penalty function and nonsmooth penalty function are investigated. By using these new smooth penalty functions, a nonlinear optimization problem with inequality constraints is converted into a sequence of minimizations of continuously differentiable function. Then based on each of the smoothed penalty functions, we develop an algorithm respectively to finding an approximate optimal solution of the original constrained optimization problem and prove the convergence of the proposed algorithms. The effectiveness of the smoothed penalty functions is illustrated through three examples, which show that the algorithm seems efficient.
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Meng, Zhiqing, Rui Shen, Chuangyin Dang, and Min Jiang. "Augmented Lagrangian Objective Penalty Function." Numerical Functional Analysis and Optimization 36, no. 11 (November 2, 2015): 1471–92. http://dx.doi.org/10.1080/01630563.2015.1070864.

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Agarwal, Vivek, Andrei V. Gribok, and Mongi A. Abidi. "Image restoration usingL1norm penalty function." Inverse Problems in Science and Engineering 15, no. 8 (December 2007): 785–809. http://dx.doi.org/10.1080/17415970600971987.

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Huyer, Waltraud, and Arnold Neumaier. "A New Exact Penalty Function." SIAM Journal on Optimization 13, no. 4 (January 2003): 1141–58. http://dx.doi.org/10.1137/s1052623401390537.

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Feiring, Bruce R., Don T. Phillips, and Gary L. Hogg. "Penalty function techniques: A tutorial." Computers & Industrial Engineering 9, no. 4 (January 1985): 307–26. http://dx.doi.org/10.1016/0360-8352(85)90019-1.

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Shandiz, Roohollah Aliakbari, and Emran Tohidi. "Decrease of the Penalty Parameter in Differentiable Penalty Function Methods." Theoretical Economics Letters 01, no. 01 (2011): 8–14. http://dx.doi.org/10.4236/tel.2011.11003.

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Zheng, Ying, Zhiqing Meng, and Rui Shen. "An M-Objective Penalty Function Algorithm Under Big Penalty Parameters." Journal of Systems Science and Complexity 29, no. 2 (August 29, 2015): 455–71. http://dx.doi.org/10.1007/s11424-015-3204-3.

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Pantoja, J. F. A. De O., and D. Q. Mayne. "Exact penalty function algorithm with simple updating of the penalty parameter." Journal of Optimization Theory and Applications 69, no. 3 (June 1991): 441–67. http://dx.doi.org/10.1007/bf00940684.

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Mongeau, Marcel, and Annick Sartenaer. "Automatic decrease of the penalty parameter in exact penalty function methods." European Journal of Operational Research 83, no. 3 (June 1995): 686–99. http://dx.doi.org/10.1016/0377-2217(93)e0339-y.

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Dissertations / Theses on the topic "Penalty function"

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Meini, Méndez Iván Fabio. "The penalty: function and requirements." Pontificia Universidad Católica del Perú, 2013. http://repositorio.pucp.edu.pe/index/handle/123456789/116002.

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Legitimacy of criminal sanction is originated on its own purposes pursued in a state governed by the Rule of Law. That legitimacy should include the penalty as well as security measures, bearing in mind that both are imposed to someone breaking a rule of conduct, and therefore, someone capable to do it. Reviewing penal capacity or criminal liability concepts is required because if penal capacity means the capacity to understand the reality and adjust the behavior to it, and if every legitimate criminal sanction have to be imposed to someone who have the capacity of break it, then security measures also have to be imposed only to people responsible, capable to understand rules and act in accordance. With regard to people not subject to criminal liability they are standing outside Criminal Law and punish them would be illegitimate. In this line, criminal liability should be seen not only as a crime assumption but also as a basic statement for any dialogue the state shall have with the citizens: at the level of crime itself, proceedings and sentence execution .
La legitimación de la sanción penal se deriva de los fines que persigue en un Estado de derecho. Dicha legitimación debe abarcar tanto a la pena como a la medida de seguridad, y tener en cuenta que tanto la pena como la medida de seguridad se imponen a quien infringe una norma de conducta y, por tanto, a quien tiene capacidad para infringirla. Esto presupone revisar el concepto de capacidad penal o imputabilidad,pues si imputabilidad es capacidad para comprender la realidad y adecuar el comportamiento a dicha comprensión, y toda sanción penal legítima ha de imponerse a quien tiene dicha capacidad, también las medidas de seguridad han de ser impuestas solo a imputables. Los verdaderos inimputables son aquellos que están al margen del derecho penal y a quienes resulta ilegítimo imponer alguna sanción. En esta línea, la imputabilidad ha de ser vista no solo como presupuesto del delito, sino como presupuesto de cualquier diálogo que tenga el Estado con el ciudadano con respecto al delito, al proceso y a la ejecución de la pena.
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Smith, Stephen Bevis. "Exact penalty function algorithms for constrained optimal control problems." Thesis, Imperial College London, 2011. http://hdl.handle.net/10044/1/7996.

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Zhao, Xiaobing. "A Penalty Function-Based Dynamic Hybrid Shop Floor Control System." Diss., The University of Arizona, 2006. http://hdl.handle.net/10150/195300.

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To cope with dynamics and uncertainties, a novel penalty function-based hybrid, multi-agent shop floor control system is proposed in this dissertation. The key characteristic of the proposed system is the capability of adaptively distributing decision-making power across different levels of control agents in response to different levels of disturbance. The subordinate agent executes tasks based on the schedule from the supervisory level agent in the absence of disturbance. Otherwise, it optimizes the original schedule before execution by revising it with regard to supervisory level performance (via penalty function) and disturbance. Penalty function, mathematical programming formulations, and quantitative metrics are presented to indicate the disturbance levels and levels of autonomy. These formulations are applied to diverse performance measurements such as completion time related metrics, makespan, and number of late jobs. The proposed control system is illustrated, tested with various job shop problems, and benchmarked against other shop floor control systems. In today's manufacturing system, man still plays an important role together with the control system Therefore, better coordination of humans and control systems is an inevitable topic. A novel BDI agent-based software model is proposed in this work to replace the partial decision-making function of a human. This proposed model is capable of 1) generating plans in real-time to adapt the system to a changing environment, 2) supporting not only reactive, but also proactive decision-making, 3) maintaining situational awareness in human language-like logic to facilitate real human decision-making, and 4) changing the commitment strategy adaptive to historical performance. The general purposes human operator model is then customized and integrated with an automated shop floor control system to serve as the error detection and recovery system. This model has been implemented in JACK software; however, JACK does not support real-time generation of a plan. Therefore, the planner sub-module has been developed in Java and then integrated with the JACK. To facilitate integration of an agent, real-human, and the environment, a distributed computing platform based on DOD High Level Architecture has been used. The effectiveness of the proposed model is then tested in several scenarios in a simulated automated manufacturing environment.
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Dew, M. C. "An exact penalty function algorithm for accurate optimisation of industrial problems." Thesis, University of Hertfordshire, 1985. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.353622.

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Ozdaryal, Burak. "Exterior Penalty Approaches for Solving Linear Programming Problems." Thesis, Virginia Tech, 1999. http://hdl.handle.net/10919/33862.

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In this research effort, we study three exterior penalty function approaches for solving linear programming problems. These methods are an active set l2 penalty approach (ASL2), an inequality-equality based l2 penalty approach (IEL2), and an augmented Lagrangian approach (ALAG). Particular effective variants are presented for each method, along with comments and experience on alternative algorithmic strategies that were empirically investigated. Our motivation is to examine the relative performance of these different approaches based on the basic l2 penalty function in order to provide insights into the viability of these methods for solving linear programs. To test the performance of these algorithms, a set of randomly generated problems as well as a set of NETLIB test problems from the public domain are used. By way of providing a benchmark for comparisons, we also solve the test problems using CPLEX 6.0, an advanced simplex implementation. While a particular variant (ALAG2) of ALAG performed the best for randomly generated test problems, ASL2 performed the best for the NETLIB test problems. Moreover, for test problems having only equality constraints, IEL2, and ASL2 (which is a finer-tuned version of IEL2 in this case) were comparable and yielded a second-best performance in comparison with ALAG2. Furthermore, a set of problems with relatively higher density parameter values, as well as a set of low-density problems were used to determine the effect of density on the relative performances of these methods. This experiment revealed that for linear programs with a high density parameter, ASL2 is the best alternative among the tested algorithms; whereas, for low-density problems ALAG2 is the fastest method. Moreover, although our implementation was rudimentary in comparison with CPLEX, all of the tested methods attained a final solution faster than CPLEX for the set of large-scale low-density problems, sometimes as fast as requiring only 16-23% of the effort consumed by CPLEX. Average rank tests based on the computational results obtained are performed using two different statistics, that assess the speed of convergence and the quality or accuracy of the solution, in order to determine the relative effectiveness of the algorithms and to validate our conclusions. Overall, the results provide insights into selecting algorithmic strategies based on problem structure and indicate that while this class of methods is viable for computing near optimal solutions, more research is needed to design robust and competitive exterior point methods for solving linear programming problems. However, the use of the proposed variant of the augmented Lagrangian method to solve large-scale low-density linear programs is promising and should be explored more extensively.
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Case, Lori Michelle. "An l??1 penalty function approach to the nonlinear bilevel programming problem." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1997. http://www.collectionscanada.ca/obj/s4/f2/dsk3/ftp04/nq21334.pdf.

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Chang, Kcomt Romy Alexandra. "Constitutional function assigned to the penalty: Bases for a criminal policy plan." Pontificia Universidad Católica del Perú, 2013. http://repositorio.pucp.edu.pe/index/handle/123456789/116385.

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This article intends to analyze treatment and functions assigned to the penalty by our Peruvian Constitution and the way this legal institution is conducted at the prescribed basic penalty level (imposed by the legislator ineach type of criminal offence), the specific penalty level (imposed by the judge according to its individual characteristics in each case) and at the penitentiary enforcement level. Finally recommends some considerations for carrying out a possible legislative reform in accordance with a criminal policy plan within our constitutional framework.
El presente trabajo busca efectuar un análisis en torno al tratamiento y las funciones que nuestra Constitución política asigna a la pena, y la manera como dicha institución se desarrolla en nuestro país con respectoa la pena abstracta (la impuesta por el legislador en cada tipo penal), la pena concreta (la impuesta por el juez luego de una individualización en cada casoconcreto), y su ejecución en el ámbito penitenciario. Finaliza proponiendo algunas consideraciones para una eventual reforma legislativa conforme conun plan de política criminal que se encuentre dentro del marco constitucional.
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Bose, Gopal Krishna 1955. "Model selection : an optimal approach to constructing a penalty function in small samples." Monash University, Dept. of Econometrics and Business Statistics, 2002. http://arrow.monash.edu.au/hdl/1959.1/8728.

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Geusa, Federica. "Temperature penalty adimensionale per piccoli e medi campi di sonde geotermiche." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2017.

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Lo scopo di questa Tesi è stato quello di contribuire allo sviluppo dei metodi di dimensionamento e di simulazione dinamica degli scambiatori verticali con il terreno mediante le g-function. Un primo contributo è stato quello di migliorare le espressioni polinomiali delle g-function determinate da Zanchini e Lazzari (E.Zanchini, S. Lazzari, “Temperature distribution in a field of long Borehole Heat Exchangers (BHEs) subjected to a monthly averaged heat flux”, Energy 59,570-580 (2013)). Sono state perciò ricavate nuove espressioni polinomiali che, a differenza delle precedenti, possono essere sommate fra loro perché valgono a partire dallo stesso istante iniziale. Sono state quindi fornite nuove tabelle di coefficienti. Sono state poi determinate e utilizzate, mediante combinazioni di g-function, espressioni matematiche adimensionali del temperature penalty per piccoli e medi campi di sonde geotermiche. Questa grandezza viene utilizzata nel metodo di dimensionamento ASHRAE. Bernier, Chahla e Pinel nel loro lavoro “Long-term ground-temperature changes in Geo-Exchange Systems. ASHRAE Transaction, 114(2), 342-50(2008)” hanno fornito tabelle di valori del temperature penalty adimensionale per quattro geometrie di campi sonde. Tali tabelle sono state qui ampliate, calcolando il temperature penalty per campi di sonde a linea singola (1x2, 1x3, 1x4, 1x5, 1x6, 1x7, 1x8), a linea doppia (2x1, 2x2, 2x3, 2x4, 2x5, 2x6, 2x7 e 2x8) e campi quadrati (3x3, 4x4, 5x5). Infine, utilizzando risultati di calcolo ottenuti utilizzando l’espressione del temperature penalty adimensionale, è stata determinata, per ciascuno dei campi analizzati, una funzione polinomiale approssimata del temperature penalty in funzione del logaritmo del tempo adimensionale. Queste espressioni polinomiali, rese disponibili mediante tabelle dei coefficienti, consentono di ridurre drasticamente i tempi di calcolo nella simulazione dinamica di lungo termine dei campi di sonde considerati.
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Soeffker, Ninja. "The Use of Probabilistic Risk Functions and Linear Penalty Functions for Hospital Evacuation Planning." Thesis, Virginia Tech, 2014. http://hdl.handle.net/10919/50918.

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In Bish et al. (2014), two approaches for the generation of hospital evacuation transportation plans were proposed: the minimization of the overall risk and the minimization of the evacuation duration. The resulting evacuation plans differ in terms of overall risk and duration, but also in the evacuation order of patients with different characteristics, the filling of hospital beds, and the assignments of the patients to the various vehicle types. Due to the computational effort of the duration minimization, manipulations of the risk functions for the risk minimization approach were searched in this thesis such that the resulting evacuation plans approach the minimal duration without rules for the assignments of patients to vehicle types. It is possible to create risk functions such that the resulting plans have shorter durations than with the basic risk functions, but the overall risk increases and other properties of the plans change. Furthermore, a new objective function was introduced in this thesis that minimizes an overall penalty function, where penalties are incurred for time intervals in which patients are at the evacuating hospital or being transported. The characteristics of the patients are considered by different weights in the penalty function. For the given problem instance, it is possible to choose penalty factors such that the overall risk is close to the minimal risk or to choose them such that the duration decreases. It is a simple approach with run times that are comparable to the risk minimization approach for the given problem instance.
Master of Science
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Books on the topic "Penalty function"

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Waldman, W. A penalty element formulation for calculating bulk stress. Melbourne, Australia: Aeronautical Research Laboratory, 1989.

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Funaro, Daniele. Convergence results for pseudospectral approximations of hyperbolic systems by a penalty type boundary treatment. Hampton, Va: National Aeronautics and Space Administration, Langley Research Center, 1989.

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Funaro, Daniele. Convergence results for pseudospectral approximations of hyperbolic systems by a penalty type boundary treatment. Hampton, Va: National Aeronautics and Space Administration, Langley Research Center, 1989.

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Bedau, Hugo Adam. Capital Punishment. Edited by Hugh LaFollette. Oxford University Press, 2009. http://dx.doi.org/10.1093/oxfordhb/9780199284238.003.0028.

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Understanding and justifying capital punishment need to proceed from within a larger framework that can be and often is left implicit. That framework consists of one's views about punishment generally; only within that context can one adequately face the narrower issues peculiar to understanding and justifying the death penalty. If punishment as such could not be justified, then a fortiori neither could the death penalty. If punishment generally serves certain purposes or functions, then presumably so does the death penalty. Not so conversely, however. The death penalty might not be justified, but that need not put in doubt the justification of punishment in general. The discussion in this article proceeds on two assumptions. First, the general features defining punishment within a legal system will be taken for granted. Secondly, the function and purposes of the death penalty will be assumed to be those shared by punishments generally.
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D, Gottlieb, and Institute for Computer Applications in Science and Engineering., eds. A stable penalty method for the compressible Navier-Stokes equations. Hampton, VA: Institute for Computer Applications in Science and Engineering, NASA Langley Research Center, 1994.

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Doyle, David M., and Liam O'Callaghan. Capital Punishment in Independent Ireland. Liverpool University Press, 2020. http://dx.doi.org/10.3828/liverpool/9781789620276.001.0001.

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This is a comprehensive and nuanced historical survey of the death penalty in Ireland from the immediate post-Civil War period through to its complete abolition. Using original archival material, this book sheds light on the various social, legal and political contexts in which the death penalty operated and was discussed. In Ireland the death penalty served a dual function: as an instrument of punishment in the civilian criminal justice system, and as a weapon to combat periodic threats to the security of the state posed by the IRA. In closely examining cases dealt with in the ordinary criminal courts, this book elucidates ideas of class, gender, community and sanity and how these factors had an impact the administration of justice. The application of the death penalty also had a strong political dimension, most evident in the enactment of emergency legislation and the setting up of military courts specifically targeted at the IRA. As this book demonstrates, the civilian and the political strands converged in the story of the abolition of the death penalty in Ireland. Long after decision-makers accepted that the death penalty was no longer an acceptable punishment for ‘ordinary’ cases of murder, lingering anxieties about the threat of subversives dictated the pace of abolition and the scope of the relevant legislation.
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Simon, Morris. 6 The Approval and Regulation of Individuals. Oxford University Press, 2016. http://dx.doi.org/10.1093/law/9780199688753.003.0006.

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This chapter concerns the approval and the regulation of individuals—specifically the senior management and customer-facing staff of a firm. Following the collapse of institutions such as Northern Rock (2007), it was agreed that the regulator should engage more intensively with firms over senior management’s competence and technical skills. This chapter considers the requirement for approval, the application process for approval, the possibility of withdrawal of approval, and the penalty for performance of a controlled function without approval. It then considers the Financial Conduct Authority’s (FCA) power to prohibit an individual from performing certain functions, or to take disciplinary action against an individual guilty of misconduct. Finally, the FCA and Prudential Regulatory Authority’s (PRA) ability to make rules of conduct, and the application of the Statements of Principle and Code of Practice for Approved Persons (APER), are discussed.
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Yaffe, Gideon. The Weight of a Legal Reason. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198803324.003.0006.

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This chapter forwards a theory of the strength of legal reasons under which how much say a person has over the law matters to how strong his legal reasons are. Three measures of strength are discussed: (1) a statutory measure, set by the severity of a statutorily specified penalty, (2) an institutional measure, set by the amount of force employed by legal institutions, and (3) an expressive measure, set by the amount of disapproval expressed by the law. The strength of a legal reason provided by a fact for a particular person, in any of these three senses, is a function of the person’s complicity in the legal facts thanks to which the fact provides a legal reason with a given strength. Complicity, in the relevant sense, it is suggested, is established by the person’s degree of say over the relevant body of legal facts.
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Smith, Peter Scharff. Prisoners’ Families, Public Opinion, and the State. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198810087.003.0008.

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This chapter moves the focus from the offender-state binary to a broader discussion about the relationship between penal policies, prisons, and society. It does so using a partly Durkheimian approach. The sociologist Émile Durkheim saw the function of the institutions of penality less as a form of instrumental rationality and more as a kind of routinized expression of emotion. According to such an approach, thinking of punishment as a calculated instrument for the rational control of conduct would be to miss its essential character, to mistake superficial form for true content since the essence of punishment is irrational, unthinking emotion fixed by a sense of the sacred and its violation. Furthermore, this chapter suggests that interpreting and implementing the rights of prisoners’ children and families provides a perspective on criminal justice systems, which can potentially change the current state-offender dynamic.
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Albertson, Kevin, Mary Corcoran, and Jake Phillips, eds. Marketisation and Privatisation in Criminal Justice. Policy Press, 2020. http://dx.doi.org/10.1332/policypress/9781447345701.001.0001.

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Criminal justice used to be thought of as a field autonomous from politics and the economy, with the management of crime and punishment being seen as essentially the responsibility of government. However, in recent decades, policies have been adopted which blur the institutional boundaries and functions of the public sector with those of for-profit and civil society interests in many parts of the penal/welfare complex. The impact of these developments on society is contested: Proponents of the ‘neo-liberal penality thesis’ argue economic deregulation, welfare retrenchment, individualised choices – and associated responsibility – may be aligned by market forces into efficient delivery of ‘law and order’. Set against the neo-liberal penal position are arguments that the corporate sector may be no more efficient in delivering criminal justice services than is the public sector, and reliance on the profit motive to deliver criminal justice may lead to perverse incentivisation of NGOs or state agencies. It is to this debate we add our contribution. Criminal justice is an ideal sector in which to consider the implications arising from the differing incentive structures held by different institutions, both private and public, citizens, governments, social enterprise and the corporate sector. All agree on the need for criminal justice, even as they compete in the policy sphere to dictate its form and delivery.
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Book chapters on the topic "Penalty function"

1

Bartholomew–Biggs, Michael. "Penalty Function Methods." In Nonlinear Optimization with Engineering Applications, 1–14. Boston, MA: Springer US, 2008. http://dx.doi.org/10.1007/978-0-387-78723-7_18.

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Choi, ByoungSeon. "Penalty Function Methods." In ARMA Model Identification, 43–74. New York, NY: Springer US, 1992. http://dx.doi.org/10.1007/978-1-4613-9745-8_3.

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Evtushenko, Yurij G. "The Penalty Function Method." In Numerical Optimization Techniques, 196–263. New York, NY: Springer New York, 1985. http://dx.doi.org/10.1007/978-1-4612-5022-7_4.

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Cuvelier, C., A. Segal, and A. A. van Steenhoven. "The penalty function method." In Finite Element Methods and Navier-Stokes Equations, 263–87. Dordrecht: Springer Netherlands, 1986. http://dx.doi.org/10.1007/978-94-010-9333-0_8.

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Si, Chengyong, Jianqiang Shen, Xuan Zou, Yashuai Duo, Lei Wang, and Qidi Wu. "A Dynamic Penalty Function for Constrained Optimization." In Advances in Swarm and Computational Intelligence, 261–72. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-20472-7_28.

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Matias, J., P. Mestre, A. Correia, P. Couto, C. Serodio, and P. Melo-Pinto. "Penalty Fuzzy Function for Derivative-Free Optimization." In Advances in Intelligent and Soft Computing, 293–301. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-24001-0_27.

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Kulkarni, Anand Jayant, Kang Tai, and Ajith Abraham. "Constrained Probability Collectives with a Penalty Function Approach." In Intelligent Systems Reference Library, 61–72. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-16000-9_4.

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Zheng, Fangying, and Liansheng Zhang. "Constrained Global Optimization Using a New Exact Penalty Function." In Springer Proceedings in Mathematics & Statistics, 69–76. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-08377-3_8.

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Coope, Ian D., and Christopher J. Price. "Exact Penalty Function Methods for Nonlinear Semi-Infinite Programming." In Nonconvex Optimization and Its Applications, 137–57. Boston, MA: Springer US, 1998. http://dx.doi.org/10.1007/978-1-4757-2868-2_5.

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Zhang, Liwei, and Huanwen Tang. "A Further Study on a Penalty Function of Bertsekas." In Applied Optimization, 345–51. Boston, MA: Springer US, 1998. http://dx.doi.org/10.1007/978-1-4613-3335-7_18.

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Conference papers on the topic "Penalty function"

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Wang, Ran, Jie He, Liyuan Xu, and Qin Wang. "Penalty Function Based Anchor-Free Positioning." In 2015 11th International Conference on Mobile Ad-hoc and Sensor Networks (MSN). IEEE, 2015. http://dx.doi.org/10.1109/msn.2015.10.

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Qin, Jiangning, and Duc Nguyen. "Generalized exponential penalty function for nonlinear programming." In 35th Structures, Structural Dynamics, and Materials Conference. Reston, Virigina: American Institute of Aeronautics and Astronautics, 1994. http://dx.doi.org/10.2514/6.1994-1360.

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Datta, Rituparna, and Kalyanmoy Deb. "Individual penalty based constraint handling using a hybrid bi-objective and penalty function approach." In 2013 IEEE Congress on Evolutionary Computation (CEC). IEEE, 2013. http://dx.doi.org/10.1109/cec.2013.6557898.

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Saroare, Md Kibria, Md Syadus Sefat, Sajib Sen, and Md Shahjahan. "A modified penalty function in fuzzy clustering algorithm." In 2017 Intelligent Systems Conference (IntelliSys). IEEE, 2017. http://dx.doi.org/10.1109/intellisys.2017.8324332.

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Zeng, Huiwen, and H. J. Trussell. "Feature Selection using a Mixed-Norm Penalty Function." In 2006 International Conference on Image Processing. IEEE, 2006. http://dx.doi.org/10.1109/icip.2006.312667.

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Demarcke, Pieterjan, and Hendrik Rogier. "Penalty function method for constrained DOA-based beamforming." In 2009 IEEE Antennas and Propagation Society International Symposium (APSURSI). IEEE, 2009. http://dx.doi.org/10.1109/aps.2009.5171466.

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Jadaan, Omar Al, Lakshmi Rajamani, and C. R. Rao. "Parameterless penalty function for solving constrained evolutionary optimization." In 2009 IEEE Workshop on Hybrid Intelligent Models and Applications (HIMA). IEEE, 2009. http://dx.doi.org/10.1109/hima.2009.4937826.

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Chen, Zhongyuan, Tao Qi, Yongbo Li, Jing Li, Chuan He, Hanhan Qian, Wei Xiang, and Zhemin Lin. "Quality Evaluation and Penalty Function of Solar Power." In 2018 International Conference on Power System Technology (POWERCON). IEEE, 2018. http://dx.doi.org/10.1109/powercon.2018.8602277.

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Fu, Yuli, Shengli Xie, and Zhaoshui He. "A Penalty Function Based Algorithm of Blind Separation." In 2006 International Conference on Computational Intelligence and Security. IEEE, 2006. http://dx.doi.org/10.1109/iccias.2006.295358.

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Hassan, Mansur, and Adam Baharum. "Modified Courant-Beltrami penalty function and its convergence." In PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON MATHEMATICAL SCIENCES AND TECHNOLOGY 2018 (MATHTECH2018): Innovative Technologies for Mathematics & Mathematics for Technological Innovation. AIP Publishing, 2019. http://dx.doi.org/10.1063/1.5136374.

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Reports on the topic "Penalty function"

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Pettit, Chris, and D. Wilson. A physics-informed neural network for sound propagation in the atmospheric boundary layer. Engineer Research and Development Center (U.S.), June 2021. http://dx.doi.org/10.21079/11681/41034.

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Abstract:
We describe what we believe is the first effort to develop a physics-informed neural network (PINN) to predict sound propagation through the atmospheric boundary layer. PINN is a recent innovation in the application of deep learning to simulate physics. The motivation is to combine the strengths of data-driven models and physics models, thereby producing a regularized surrogate model using less data than a purely data-driven model. In a PINN, the data-driven loss function is augmented with penalty terms for deviations from the underlying physics, e.g., a governing equation or a boundary condition. Training data are obtained from Crank-Nicholson solutions of the parabolic equation with homogeneous ground impedance and Monin-Obukhov similarity theory for the effective sound speed in the moving atmosphere. Training data are random samples from an ensemble of solutions for combinations of parameters governing the impedance and the effective sound speed. PINN output is processed to produce realizations of transmission loss that look much like the Crank-Nicholson solutions. We describe the framework for implementing PINN for outdoor sound, and we outline practical matters related to network architecture, the size of the training set, the physics-informed loss function, and challenge of managing the spatial complexity of the complex pressure.
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