Search results for "Nonlinear programming"
showing 10 items of 31 documents
Localization of 2D Cameras in a Known Environment Using Direct 2D-3D Registration
2014
International audience; In this paper we propose a robust and direct 2D-to- 3D registration method for localizing 2D cameras in a known 3D environment. Although the 3D environment is known, localizing the cameras remains a challenging problem that is particularly undermined by the unknown 2D-3D correspondences, outliers, scale ambiguities and occlusions. Once the cameras are localized, the Structure-from-Motion reconstruction obtained from image correspondences is refined by means of a constrained nonlinear optimization that benefits from the knowledge of the scene. We also propose a common optimization framework for both localization and refinement steps in which projection errors in one v…
Energy efficient optimisation for large‐scale multiple‐antenna system with WPT
2018
In this study, an energy-efficient optimisation scheme for a large-scale multiple-antenna system with wireless power transfer (WPT) is presented. In the considered system, the user is charged by a base station with a large number of antennas via downlink WPT and then utilises the received power to carry out uplink data transmission. Novel antenna selection, time allocation and power allocation schemes are presented to optimise the energy efficiency of the overall system. In addition, the authors also consider channel state information cannot be perfectly obtained when designing the resource allocation schemes. The non-linear fractional programming-based algorithm is utilised to address the …
A fuzzy decision support tool for demand forecasting
2007
In this paper we present a decision support forecasting system to work with univariate time series based on the generalized exponential smoothing (Holt-Winters) approach. It is conceived as an integrated tool which has been implemented in Visual Basic. For improving the accuracy of the automatic forecasting it uses an optimization-based scheme which unifies the stages of estimation of the parameters and selects the best method using a fuzzy multicriteria approach. The elements of the set of local minima of the non-linear programming problems allow us to build the membership functions of the conflicting objectives. A set of real data is analyzed to show the performance of our forecasting too…
Peak Power Demand and Energy Consumption Reduction Strategies for Trains under Moving Block Signalling System
2013
Published version of an article in the journal: Mathematical Problems in Engineering. Also available from the publisher at: http://dx.doi.org/10.1155/2013/940936 Open Access In the moving block signalling (MBS) system where the tracking target point of the following train is moving forward with its leading train, overload of the substations occurs when a dense queue of trains starts (or restarts) in very close distance interval. This is the peak power demand problem. Several methods have been attempted in the literature to deal with this problem through changing train's operation strategies. However, most existing approaches reduce the service quality. In this paper, two novel approaches - …
Machining Economics and Optimization
2008
This chapter provides comprehensive knowledge regarding economical considerations and possible optimization methods of machining operations. The background of machining economics, including costs, time and productivity, related for typical machining operations (such as turning, milling and drilling) is outlined. The components of machining costs and time related to the cutting speed are distinguished, and appropriate mathematical models are presented. Optimization procedures allowing selection of optimal values of cutting speed and feed rate based on tool life and energy efficiency criteria are overviewed. In the first case, the economic cutting speed and cutting speed corresponding to the …
An LP-based hyperparameter optimization model for language modeling
2018
In order to find hyperparameters for a machine learning model, algorithms such as grid search or random search are used over the space of possible values of the models hyperparameters. These search algorithms opt the solution that minimizes a specific cost function. In language models, perplexity is one of the most popular cost functions. In this study, we propose a fractional nonlinear programming model that finds the optimal perplexity value. The special structure of the model allows us to approximate it by a linear programming model that can be solved using the well-known simplex algorithm. To the best of our knowledge, this is the first attempt to use optimization techniques to find per…
Improving the Representativeness of a Simple Random Sample: An Optimization Model and Its Application to the Continuous Sample of Working Lives
2020
This paper proposes an optimization model for selecting a larger subsample that improves the representativeness of a simple random sample previously obtained from a population larger than the population of interest. The problem formulation involves convex mixed-integer nonlinear programming (convex MINLP) and is, therefore, NP-hard. However, the solution is found by maximizing the size of the subsample taken from a stratified random sample with proportional allocation and restricting it to a p-value large enough to achieve a good fit to the population of interest using Pearson&rsquo
Comparative evaluation of some interactive reference point-based methods for multi-objective optimisation
1999
Many real-world optimisation applications include several conflicting objectives of possibly nondifferentiable character. However, the lack of computationally efficient, interactive methods for nondifferentiable multi-objective optimisation problems is apparent. To satisfy this demand, a method called NIMBUS has been developed. Two versions of the basic method are presented and compared both theoretically and computationally. In order to give variety to the comparison, a related approach, called reference direction method is included. Theoretically, the methods differ in handling the information requested from the user. Numerical experiments indicate differences in computational efficiency …
Improving demand forecasting accuracy using nonlinear programming software
2006
We address the problem of forecasting real time series with a proportion of zero values and a great variability among the nonzero values. In order to calculate forecasts for a time series, the model coefficients must be estimated. The appropriate choice of values for the smoothing parameters in exponential smoothing methods relies on the minimization of the fitting errors of historical data. We adapt the generalized Holt–Winters formulation so that it can consider the starting values of the local components of level, trend and seasonality as decision variables of the nonlinear programming problem associated with this forecasting procedure. A spreadsheet model is used to solve the problems o…
Scatter Search and Local NLP Solvers: A Multistart Framework for Global Optimization
2007
The algorithm described here, called OptQuest/NLP or OQNLP, is a heuristic designed to find global optima for pure and mixed integer nonlinear problems with many constraints and variables, where all problem functions are differentiable with respect to the continuous variables. It uses OptQuest, a commercial implementation of scatter search developed by OptTek Systems, Inc., to provide starting points for any gradient-based local solver for nonlinear programming (NLP) problems. This solver seeks a local solution from a subset of these points, holding discrete variables fixed. The procedure is motivated by our desire to combine the superior accuracy and feasibility-seeking behavior of gradie…