A cooperative game theory analysis for transmission loss allocation

This paper presents an analysis and discussion, based on cooperative game theory, for the allocation of the cost of losses to generators and demands in transmission systems. We construct a cooperative game theory model in which the players are represented by equivalent bilateral exchanges and we search for a unique loss allocation solution, the Core. Other solution concepts, such as the Shapley Value, the Bilateral Shapley Value and the Kernel are also explored. Our main objective is to illustrate why is not possible to find an optimal solution for allocating the cost of losses to the users of a network. Results and relevant conclusions are presented for a 4-bus system and a 14-bus system. (c) 2007 Elsevier B.V. All rights reserved.

Necessary conditions for optimal impulsive control problems

A Maximum Principle is derived for a class of optimal control problems arising in midcourse guidance, in which certain controls are represented by measures and, the state trajectories are functions of bounded variation. The optimality conditions improves on previous optimality conditions by allowing nonsmooth data, measurable time dependence, and a possibly time varying constraint set for the conventional controls.

Optimal design of smart structures using bonded piezoelectrics for vibration control

Smart material technology has become an area of increasing interest for the development of lighter and stronger structures which are able to incorporate actuator and sensor capabilities for collocated control. In the design of actively controlled structures, the determination of the actuator locations and the controller gains, is a very important issue. For that purpose, smart material modelling, modal analysis methods, control and optimization techniques are the most important ingredients to be taken into account. The optimization problem to be solved in this context presents two interdependent aspects. The first one is related to the discrete optimal actuator location selection problem, which is solved in this paper using genetic algorithms. The second is represented by a continuous variable optimization problem, through which the control gains are determined using classical techniques. A cantilever Euler-Bernoulli beam is used to illustrate the presented methodology.

A new solution to the optimal power flow problem

A new approach to solving the Optimal Power Flow problem is described, making use of some recent findings, especially in the area of primal-dual methods for complex programming. In this approach, equality constraints are handled by Newton's method inequality constraints for voltage and transformer taps by the logarithmic barrier method and the other inequality constraints by the augmented Lagrangian method. Numerical test results are presented, showing the effective performance of this algorithm. © 2001 IEEE.

Optimal Boussinesq model for shallow-water waves interacting with a microstructure

In this paper, we consider the propagation of water waves in a long-wave asymptotic regime, when the bottom topography is periodic on a short length scale. We perform a multiscale asymptotic analysis of the full potential theory model and of a family of reduced Boussinesq systems parametrized by a free parameter that is the depth at which the velocity is evaluated. We obtain explicit expressions for the coefficients of the resulting effective Korteweg-de Vries (KdV) equations. We show that it is possible to choose the free parameter of the reduced model so as to match the KdV limits of the full and reduced models. Hence the reduced model is optimal regarding the embedded linear weakly dispersive and weakly nonlinear characteristics of the underlying physical problem, which has a microstructure. We also discuss the impact of the rough bottom on the effective wave propagation. In particular, nonlinearity is enhanced and we can distinguish two regimes depending on the period of the bottom where the dispersion is either enhanced or reduced compared to the flat bottom case. © 2007 The American Physical Society.

When less is better: Insights from the product mix dilemma from the Theory of Constraints perspective

Perhaps due to its origins in a production scheduling software called Optimised Production Technology (OPT), plus the idea of focusing on system constraints, many believe that the Theory of Constraints (TOC) has a vocation for optimal solutions. Those who assess TOC according to this perspective indicate that it guarantees an optimal solution only in certain circumstances. In opposition to this view and founded on a numeric example of a production mix problem, this paper shows, by means of TOC assumptions, why the TOC should not be compared to methods intended to seek optimal or the best solutions, but rather sufficiently good solutions, possible in non-deterministic environments. Moreover, we extend the range of relevant literature on product mix decision by introducing a heuristic based on the uniquely identified work that aims at achieving feasible solutions according to the TOC point of view. The heuristic proposed is tested on 100 production mix problems and the results are compared with the responses obtained with the use of Integer Linear Programming. The results show that the heuristic gives good results on average, but performance falls sharply in some situations. © 2013 Copyright Taylor and Francis Group, LLC.

Optimal fleet configuration in San Miguel Bay, Philippines: a simple linear programming approach

Includes bibliography

Despacho ótimo de potências ativa e reativa de sistema elétricos multi-áreas considerando restrições físicas, econômicas e ambientais =: Envronmentally constrained active-reactive optimal power flow-a compromising strategy for economic-emission dispatch and a multi-area paradigm

Pós-graduação em Engenharia Elétrica - FEIS

Applications of Linear Programming to Coding Theory

Maximum-likelihood decoding is often the optimal decoding rule one can use, but it is very costly to implement in a general setting. Much effort has therefore been dedicated to find efficient decoding algorithms that either achieve or approximate the error-correcting performance of the maximum-likelihood decoder. This dissertation examines two approaches to this problem. In 2003 Feldman and his collaborators defined the linear programming decoder, which operates by solving a linear programming relaxation of the maximum-likelihood decoding problem. As with many modern decoding algorithms, is possible for the linear programming decoder to output vectors that do not correspond to codewords; such vectors are known as pseudocodewords. In this work, we completely classify the set of linear programming pseudocodewords for the family of cycle codes. For the case of the binary symmetric channel, another approximation of maximum-likelihood decoding was introduced by Omura in 1972. This decoder employs an iterative algorithm whose behavior closely mimics that of the simplex algorithm. We generalize Omura's decoder to operate on any binary-input memoryless channel, thus obtaining a soft-decision decoding algorithm. Further, we prove that the probability of the generalized algorithm returning the maximum-likelihood codeword approaches 1 as the number of iterations goes to infinity.

Paternal Care Decreases Foraging Activity and Body Condition, but Does Not Impose Survival Costs to Caring Males in a Neotropical Arachnid

Exclusive paternal care is the rarest form of parental investment in nature and theory predicts that the maintenance of this behavior depends on the balance between costs and benefits to males. Our goal was to assess costs of paternal care in the harvestman Iporangaia pustulosa, for which the benefits of this behavior in terms of egg survival have already been demonstrated. We evaluated energetic costs and mortality risks associated to paternal egg-guarding in the field. We quantified foraging activity of males and estimated how their body condition is influenced by the duration of the caring period. Additionally, we conducted a one-year capture-mark-recapture study and estimated apparent survival probabilities of caring and non-caring males to assess potential survival costs of paternal care. Our results indicate that caring males forage less frequently than non-caring individuals (males and females) and that their body condition deteriorates over the course of the caring period. Thus, males willing to guard eggs may provide to females a fitness-enhancing gift of cost-free care of their offspring. Caring males, however, did not show lower survival probabilities when compared to both non-caring males and females. Reduction in mortality risks as a result of remaining stationary, combined with the benefits of improving egg survival, may have played an important and previously unsuspected role favoring the evolution of paternal care. Moreover, males exhibiting paternal care could also provide an honest signal of their quality as offspring defenders, and thus female preference for caring males could be responsible for maintaining the trait.

A Law and Economics Analysis of Lobbying Regulation Towards an optimal structure through the Cost Indicator Index

This research primarily represents a contribution to the lobbying regulation research arena. It introduces an index which for the first time attempts to measure the direct compliance costs of lobbying regulation. The Cost Indicator Index (CII) offers a brand new platform for qualitative and quantitative assessment of adopted lobbying laws and proposals of those laws, both in the comparative and the sui generis dimension. The CII is not just the only new tool introduced in the last decade, but it is the only tool available for comparative assessments of the costs of lobbying regulations. Beside the qualitative contribution, the research introduces an additional theoretical framework for complementary qualitative analysis of the lobbying laws. The Ninefold theory allows a more structured assessment and classification of lobbying regulations, both by indication of benefits and costs. Lastly, this research introduces the Cost-Benefit Labels (CBL). These labels might improve an ex-ante lobbying regulation impact assessment procedure, primarily in the sui generis perspective. In its final part, the research focuses on four South East European countries (Slovenia, Serbia, Montenegro and Macedonia), and for the first time brings them into the discussion and calculates their CPI and CII scores. The special focus of the application was on Serbia, whose proposal on the Law on Lobbying has been extensively analysed in qualitative and quantitative terms, taking into consideration specific political and economic circumstances of the country. Although the obtained results are of an indicative nature, the CII will probably find its place within the academic and policymaking arena, and will hopefully contribute to a better understanding of lobbying regulations worldwide.

Management control systems : subcomponents, optimal design and the role of time as a contingency

Management Control System (MCS) research is undergoing turbulent times. For a long time related to cybernetic instruments of management accounting only, MCS are increasingly seen as complex systems comprising not only formal accounting-driven instruments, but also informal mechanisms of control based on organizational culture. But not only have the means of MCS changed; researchers increasingly ap-ply MCS to organizational goals other than strategy implementation.rnrnTaking the question of "How do I design a well-performing MCS?" as a starting point, this dissertation aims at providing a comprehensive and integrated overview of the "current-state" of MCS research. Opting for a definition of MCS, broad in terms of means (all formal as well as informal MCS instruments), but focused in terms of objectives (behavioral control only), the dissertation contributes to MCS theory by, a) developing an integrated (contingency) model of MCS, describing its contingencies, as well as its subcomponents, b) refining the equifinality model of Gresov/Drazin (1997), c) synthesizing research findings from contingency and configuration research concerning MCS, taking into account case studies on research topics such as ambi-dexterity, equifinality and time as a contingency.

Patches of Bare Ground as a Staple Commodity for Declining Ground-Foraging Insectivorous Farmland Birds

Conceived to combat widescale biodiversity erosion in farmland, agri-environment schemes have largely failed to deliver their promises despite massive financial support. While several common species have shown to react positively to existing measures, rare species have continued to decline in most European countries. Of particular concern is the status of insectivorous farmland birds that forage on the ground. We modelled the foraging habitat preferences of four declining insectivorous bird species (hoopoe, wryneck, woodlark, common redstart) inhabiting fruit tree plantations, orchards and vineyards. All species preferred foraging in habitat mosaics consisting of patches of grass and bare ground, with an optimal, species-specific bare ground coverage of 30–70% at the foraging patch scale. In the study areas, birds thrived in intensively cultivated farmland where such ground vegetation mosaics existed. Not promoted by conventional agri-environment schemes until now, patches of bare ground should be implemented throughout grassland in order to prevent further decline of insectivorous farmland birds.

Enhancing Sensitivity In Natural Product Nmr: Exploring Optimal Non-Uniform Sampling

Recent optimizations of NMR spectroscopy have focused their attention on innovations in new hardware, such as novel probes and higher field strengths. Only recently has the potential to enhance the sensitivity of NMR through data acquisition strategies been investigated. This thesis has focused on the practice of enhancing the signal-to-noise ratio (SNR) of NMR using non-uniform sampling (NUS). After first establishing the concept and exact theory of compounding sensitivity enhancements in multiple non-uniformly sampled indirect dimensions, a new result was derived that NUS enhances both SNR and resolution at any given signal evolution time. In contrast, uniform sampling alternately optimizes SNR (t < 1.26T2) or resolution (t~3T2), each at the expense of the other. Experiments were designed and conducted on a plant natural product to explore this behavior of NUS in which the SNR and resolution continue to improve as acquisition time increases. Possible absolute sensitivity improvements of 1.5 and 1.9 are possible in each indirect dimension for matched and 2x biased exponentially decaying sampling densities, respectively, at an acquisition time of ¿T2. Recommendations for breaking into the linear regime of maximum entropy (MaxEnt) are proposed. Furthermore, examination into a novel sinusoidal sampling density resulted in improved line shapes in MaxEnt reconstructions of NUS data and comparable enhancement to a matched exponential sampling density. The Absolute Sample Sensitivity derived and demonstrated here for NUS holds great promise in expanding the adoption of non-uniform sampling.

The Optimal Confidence Region for a Random Parameter

Under a two-level hierarchical model, suppose that the distribution of the random parameter is known or can be estimated well. Data are generated via a fixed, but unobservable realization of this parameter. In this paper, we derive the smallest confidence region of the random parameter under a joint Bayesian/frequentist paradigm. On average this optimal region can be much smaller than the corresponding Bayesian highest posterior density region. The new estimation procedure is appealing when one deals with data generated under a highly parallel structure, for example, data from a trial with a large number of clinical centers involved or genome-wide gene-expession data for estimating individual gene- or center-specific parameters simultaneously. The new proposal is illustrated with a typical microarray data set and its performance is examined via a small simulation study.