988 resultados para short-selling constraints


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This article describes and compares three heuristics for a variant of the Steiner tree problem with revenues, which includes budget and hop constraints. First, a greedy method which obtains good approximations in short computational times is proposed. This initial solution is then improved by means of a destroy-and-repair method or a tabu search algorithm. Computational results compare the three methods in terms of accuracy and speed. (C) 2007 Elsevier B.V. All rights reserved.

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This paper has two original contributions. First, we show that the present value model (PVM hereafter), which has a wide application in macroeconomics and fi nance, entails common cyclical feature restrictions in the dynamics of the vector error-correction representation (Vahid and Engle, 1993); something that has been already investigated in that VECM context by Johansen and Swensen (1999, 2011) but has not been discussed before with this new emphasis. We also provide the present value reduced rank constraints to be tested within the log-linear model. Our second contribution relates to forecasting time series that are subject to those long and short-run reduced rank restrictions. The reason why appropriate common cyclical feature restrictions might improve forecasting is because it finds natural exclusion restrictions preventing the estimation of useless parameters, which would otherwise contribute to the increase of forecast variance with no expected reduction in bias. We applied the techniques discussed in this paper to data known to be subject to present value restrictions, i.e. the online series maintained and up-dated by Shiller. We focus on three different data sets. The fi rst includes the levels of interest rates with long and short maturities, the second includes the level of real price and dividend for the S&P composite index, and the third includes the logarithmic transformation of prices and dividends. Our exhaustive investigation of several different multivariate models reveals that better forecasts can be achieved when restrictions are applied to them. Moreover, imposing short-run restrictions produce forecast winners 70% of the time for target variables of PVMs and 63.33% of the time when all variables in the system are considered.

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We consider the contributions of the exotic quarks and gauge bosons to the mass difference between the short- and the long-lived neutral kaon states in the SU(3)C×SU(3)L×U(1)N model. The lower bound MZ′∼14 TeV is obtained for the extra neutral gauge boson Z′0. Ranges for values of one of the exotic quark masses and quark mixing parameters are also presented.

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The Predispatch model (PD) calculates a short-term generation policy for power systems. In this work a PD model is proposed that improves two modeling aspects generally neglected in the literature: voltage/reactive power constraints and ramp rate constraints for generating units. Reactive power constraints turn the PD into a non-linear problem and the ramp rate constraints couple the problem dynamically in time domain. The solution of the PD is turned into a harder task when such constraints are introduced. The dual decomposition/ lagrangian relaxation technique is used in the solution approach for handing dynamic constraints. As a result the PD is decomposed into a series of independent Optimal Power Flow (FPO) sub problems, in which the reactive power is represented in detail. The solution of the independent FPO is coordinated by means of Lagrange multipliers, so that dynamic constraints are iteratively satisfied. Comparisons between dispatch policies calculated with and without the representation of ramp rate constraints are performed, using the IEEE 30 bus test system. The results point-out the importance of representing such constraints in the generation dispatch policy. © 2004 IEEE.

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This paper presents a mixed integer nonlinear programming multiobjective model for short-term planning of distribution networks that considers in an integrated manner the following planning activities: allocation of capacitor banks; voltage regulators; the cable replacement of branches and feeders. The objective functions considered in the proposed model are: to minimize operational and investment costs and minimize the voltage deviations in the the network buses, subject to a set of technical and operational constraints. A multiobjective genetic algorithm based on a Non-Dominated Sorting Genetic Algorithm (NSGA-II) is proposed to solve this model. The proposed mathematical model and solution methodology is validated testing a medium voltage distribution system with 135 buses. © 2013 Brazilian Society for Automatics - SBA.

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We consider a discrete-time financial model in a general sample space with penalty costs on short positions. We consider a friction market closely related to the standard one except that withdrawals from the portfolio value proportional to short positions are made. We provide necessary and sufficient conditions for the nonexistence of arbitrages in this situation and for a self-financing strategy to replicate a contingent claim. For the finite-sample space case, this result leads to an explicit and constructive procedure for obtaining perfect hedging strategies.

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In this paper, we address the problem of defining the product mix in order to maximise a system's throughput. This problem is well known for being NP-Complete and therefore, most contributions to the topic focus on developing heuristics that are able to obtain good solutions for the problem in a short CPU time. In particular, constructive heuristics are available for the problem such as that by Fredendall and Lea, and by Aryanezhad and Komijan. We propose a new constructive heuristic based on the Theory of Constraints and the Knapsack Problem. The computational results indicate that the proposed heuristic yields better results than the existing heuristic.

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In process industries, make-and-pack production is used to produce food and beverages, chemicals, and metal products, among others. This type of production process allows the fabrication of a wide range of products in relatively small amounts using the same equipment. In this article, we consider a real-world production process (cf. Honkomp et al. 2000. The curse of reality – why process scheduling optimization problems are diffcult in practice. Computers & Chemical Engineering, 24, 323–328.) comprising sequence-dependent changeover times, multipurpose storage units with limited capacities, quarantine times, batch splitting, partial equipment connectivity, and transfer times. The planning problem consists of computing a production schedule such that a given demand of packed products is fulfilled, all technological constraints are satisfied, and the production makespan is minimised. None of the models in the literature covers all of the technological constraints that occur in such make-and-pack production processes. To close this gap, we develop an efficient mixed-integer linear programming model that is based on a continuous time domain and general-precedence variables. We propose novel types of symmetry-breaking constraints and a preprocessing procedure to improve the model performance. In an experimental analysis, we show that small- and moderate-sized instances can be solved to optimality within short CPU times.

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The paper analyzes how to comply with an emission constraint, which restricts the use of an established energy technique, given the two options to save energy and to invest in two alternative energy techniques. These techniques differ in their deterioration rates and the investment lags of the corresponding capital stocks. Thus, the paper takes a medium-term perspective on climate change mitigation, where the time horizon is too short for technological change to occur, but long enough for capital stocks to accumulate and deteriorate. It is shown that, in general, only one of the two alternative techniques prevails in the stationary state, although, both techniques might be utilized during the transition phase. Hence, while in a static economy only one technique is efficient, this is not necessarily true in a dynamic economy.

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We investigate causes of the stratigraphic variation revealed in a 177 km, 400 MHz short-pulse radar profile of firn from West Antarctica. The profile covers 56 m depth, and its direction was close to those of the ice flow and mean wind. The average, near-surface accumulation rates calculated from the time delays of one radar horizon consistently show minima on leeward slopes and maxima on windward slopes, confirming an earlier study based on stake observations. The stratigraphic variation includes up to 30 m depth variation in individual horizons over tens of km, fold limbs that become progressively steeper with depth, and fold-hinge loci that change direction or propagate down-ice with depth over distances far less than predicted by the ice speeds. We use an accumulation rate model to show how local rate anomalies and the effect of ice speed upon a periodic variation in accumulation rate cause these phenomena, and we reproduce two key features seen in the stratigraphic variations. We conclude that the model provides an explanation of changes in spatial stratigraphy and local measures of accumulation history given the constraints of surface topography, ice and wind velocities, and a general accumulation rate for an area.

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Due to the ongoing trend towards increased product variety, fast-moving consumer goods such as food and beverages, pharmaceuticals, and chemicals are typically manufactured through so-called make-and-pack processes. These processes consist of a make stage, a pack stage, and intermediate storage facilities that decouple these two stages. In operations scheduling, complex technological constraints must be considered, e.g., non-identical parallel processing units, sequence-dependent changeovers, batch splitting, no-wait restrictions, material transfer times, minimum storage times, and finite storage capacity. The short-term scheduling problem is to compute a production schedule such that a given demand for products is fulfilled, all technological constraints are met, and the production makespan is minimised. A production schedule typically comprises 500–1500 operations. Due to the problem size and complexity of the technological constraints, the performance of known mixed-integer linear programming (MILP) formulations and heuristic approaches is often insufficient. We present a hybrid method consisting of three phases. First, the set of operations is divided into several subsets. Second, these subsets are iteratively scheduled using a generic and flexible MILP formulation. Third, a novel critical path-based improvement procedure is applied to the resulting schedule. We develop several strategies for the integration of the MILP model into this heuristic framework. Using these strategies, high-quality feasible solutions to large-scale instances can be obtained within reasonable CPU times using standard optimisation software. We have applied the proposed hybrid method to a set of industrial problem instances and found that the method outperforms state-of-the-art methods.

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The Ivrea–Verbano Zone (IVZ), northern Italy, exposes an attenuated section through the Permian lower crust that records high-temperature metamorphism under lower crustal conditions and a protracted history of extension and exhumation associated partly with the Jurassic opening of the Alpine Tethys ocean. This study presents SHRIMP U–Pb geochronology of rutile from seven granulite facies metapelites from the base of the IVZ, collected from locations spanning ~35 km along the strike of Paleozoic fabrics. Rutile crystallised during Permian high-temperature metamorphism and anatexis, yet all samples give Jurassic rutile U–Pb ages that record cooling through 650–550 °C. Rutile age distributions are dominated by a peak at ~160 Ma, with a subordinate peak at ~175 Ma. Both ~160 and ~175 Ma age populations show excellent agreement between samples, indicating that the two distinctive cooling stages they record were synchronous on a regional scale. The ~175 Ma population is interpreted to record cooling in the footwall of rift-related faults and shear zones, for which widespread activity in the Lower Jurassic has been documented along the western margin of the Adriatic plate. The ~160 Ma age population postdates the activity of all known rift-related structures within the Adriatic margin, but coincides with extensive gabbroic magmatism and exhumation of sub-continental mantle to the floor of the Alpine Tethys, west of the Ivrea Zone. We propose that this ~160 Ma early post-rift age population records regional cooling following episodic heating of the distal Adriatic margin, likely related to extreme lithospheric thinning and associated advection of the asthenosphere to shallow levels. The partial preservation of the ~175 Ma age cluster suggests that the post-rift (~160 Ma) heating pulse was of short duration. The regional consistency of the data presented here, which is in contrast to many other thermochronometers in the IVZ, demonstrates the value of the rutile U–Pb technique for probing the thermal evolution of high-grade metamorphic terrains. In the IVZ, a significant decoupling between Zr-in-rutile temperatures and U–Pb ages of rutile is observed, with the two systems recording events ~120 Ma apart.