Search results for "Linear programming"
showing 10 items of 137 documents
New descent rules for solving the linear semi-infinite programming problem
1994
The algorithm described in this paper approaches the optimal solution of a continuous semi-infinite linear programming problem through a sequence of basic feasible solutions. The descent rules that we present for the improvement step are quite different when one deals with non-degenerate or degenerate extreme points. For the non-degenerate case we use a simplex-type approach, and for the other case a search direction scheme is applied. Some numerical examples illustrating the method are given.
The OptQuest Callable Library
2005
In this chapter we discuss the development and application of a library of functions that is the optimization engine for the OptQuest system. OptQuest is commercial software designed for optimizing complex systems, such as those formulated as simulation models. OptQuest has been integrated with several simulation packages with the goal of adding optimization capabilities. The optimization technology within OptQuest is based on the metaheuristic framework known as scatter search. In addition to describing the functionality of the OptQuest Callable Library (OCL) with an illustrative example, we apply it to a set of unconstrained nonlinear optimization problems.
Fast and Accurate Bounds on Linear Programs
2009
We present an algorithm that certifies the feasibility of a linear program while using rational arithmetic as little as possible. Our approach relies on computing a feasible solution of the linear program that is as far as possible from satisfying an inequality at equality. To realize such an approach, we have to detect the set of inequalities that can only be satisfied at equality. Compared to previous approaches for this problem our algorithm has a much higher rate of success.
Certifying feasibility and objective value of linear programs
2012
Abstract We present an algorithm that certifies the feasibility of a linear program and computes a safe bound on its objective value while using rational arithmetic as little as possible. Our approach relies on computing a feasible solution that is as far as possible from satisfying an inequality at equality. To this end, we have to detect the set of inequalities that can only be satisfied at equality. Compared to previous approaches, our algorithm has a much higher success rate.
Black-Box Solvers
2017
Linear programming is perhaps the best-known tool for optimization. Linear programming is a general-purpose framework that allows a real system to be abstracted as a model with a linear objective function subject to a set of linear constraints.
Optimization of polygeneration plants and μ-grids for civil applications
2010
The problem of combined energy production and distribution of warm and cold fluids is very complex because it includes two possible configurations, the small single unit for individual buildings and the large plant integrated with district heating networks. Dealing with such a complex problem, involving a very large number of variables, requires efficient algorithms and resolution techniques. The present study illustrates a MILP approach to the optimization of synthesis, design and operation for CHCP-based μ-grids including thermal energy storages. The proposed approach develops a method for designing and optimizing district energy systems, starting with the information available for the di…
Network-Assisted Resource Allocation with Quality and Conflict Constraints for V2V Communications
2018
The 3rd Generation Partnership Project (3GPP) has recently established in Rel. 14 a network-assisted resource allocation scheme for vehicular broadcast communications. Such novel paradigm is known as vehicle--to--vehicle (V2V) \textit{mode-3} and consists in eNodeBs engaging only in the distribution of sidelink subchannels among vehicles in coverage. Thereupon, without further intervention of the former, vehicles will broadcast their respective signals directly to their counterparts. Because the allotment of subchannels takes place intermittently to reduce signaling, it must primarily be conflict-free in order not to jeopardize the reception of signals. We have identified four pivotal types…
SIOPRED performance in a Forecasting Blind Competition
2012
In this paper we present the results obtained by applying our automatic forecasting support system, named SIOPRED, over a data set of time series in a Forecasting Blind Competition. In order to apply our procedure for providing point forecasts it has been necessary to develop an interactive strategy for the choice of the suitable length of the seasonal cycle and the seasonality form for a generalized exponential smoothing method, which have been obtained using SIOPRED. For the choice of those essential characteristics of forecasting methods, also a certain multi-objective formulation which minimizes several measures of fitting is used. Once these specifications are established, the model pa…
Reassessing Accuracy Rates of Median Decisions
2007
We show how Bruno de Finetti''s fundamental theorem of prevision has computable applications in statistical problems that involve only partial information. Specifically, we assess accuracy rates for median decision procedures used in the radiological diagnosis of asbestosis. Conditional exchangeability of individual radiologists'' diagnoses is recognized as more appropriate than independence which is commonly presumed. The FTP yields coherent bounds on probabilities of interest when available information is insufficient to determine a complete distribution. Further assertions that are natural to the problem motivate a partial ordering of conditional probabilities, extending the computation …
Assessing uncertainty of voter transitions estimated from aggregated data. Application to the 2017 French presidential election
2020
[EN] Inferring electoral individual behaviour from aggregated data is a very active research area, with ramifications in sociology and political science. A new approach based on linear programming is proposed to estimate voter transitions among parties (or candidates) between two elections. Compared to other linear and quadratic programming models previously published, our approach presents two important innovations. Firstly, it explicitly deals with new entries and exits in the election census without assuming unrealistic hypotheses, enabling a reasonable estimation of vote behaviour of young electors voting for the first time. Secondly, by exploiting the information contained in the model…