An analysis of the hydraulic behavior of pipe networks often involves imprecise or uncertain quantities. Typical examples of these quantities are the roughness coefficient of old pipes, which becomes increasingly diff...
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An analysis of the hydraulic behavior of pipe networks often involves imprecise or uncertain quantities. Typical examples of these quantities are the roughness coefficient of old pipes, which becomes increasingly difficult to determine as the network ages, and the demands of the network, which can vary significantly according to the number of users connected to the network. These are quantities for which there is often only semiquantitative information which generally implies a degree of subjectiveness and that cannot therefore be expressed either with precise values or through statistical distributions. In this article we show how the fuzzy set theory provides conceptual tools for one to deal with this kind of information and to calculate how the uncertainties of the available information can spread to the unknowns of the problem, that is, to the discharges and piezometric heads. After a brief review of the fuzzy set theory, the way the hydraulic problem can be described within a fuzzy approach framework is given. Following this review, a suitable method, based on interval algebra and optimization theory, is introduced to solve the corresponding fuzzy equations and it is illustrated through examples.
We consider the problem of minimization of energy dissipation in a conductive electromagnetic medium with a fixed geometry and a priori given lower and upper bounds for the conductivity. The nonlinear optimization pro...
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We consider the problem of minimization of energy dissipation in a conductive electromagnetic medium with a fixed geometry and a priori given lower and upper bounds for the conductivity. The nonlinear optimization problem is analyzed by using the primal-dual Newton interior-point method. The elliptic differential equation for the electric potential is considered as an equality constraint. Transforming iterations for the null space decomposition of the condensed primal-dual system are applied to find the search direction. The numerical experiments treat two-dimensional isotropic systems.
In this paper, a simple searching approach integrated the nonlinear programming problem and the modified grey relational analysis is proposed to find the near-optimal and collision-free path for a robot, from an initi...
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In this paper, a simple searching approach integrated the nonlinear programming problem and the modified grey relational analysis is proposed to find the near-optimal and collision-free path for a robot, from an initial position to a goal position, in which the robot can be acted in the known or unknown workspace with multiple circular obstacles. The proposed find-path procedure consists of at least one trial. Each trial includes three main stages, i.e., a forward search stage, a backward search stage, and an inference stage. After all trials are completed, a decision-making stage is introduced to determine the near-optimal and collision-free path which is guaranteed to reach the goal. Besides, the presented method is applicable for the on-line applications and, furthermore, can solve the local minimal problems. Simulation results for circular obstacles demonstrate the performances of the proposed approach and its potential as an on-line path planner.
The Dual Active Set Algorithm (DASA), presented in Hager, Advances in Optimization and Parallel Computing, P.M. Pardalos (Ed.), North Holland: Amsterdam, 1992, pp. 137-142, for strictly convex optimization problems, i...
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The Dual Active Set Algorithm (DASA), presented in Hager, Advances in Optimization and Parallel Computing, P.M. Pardalos (Ed.), North Holland: Amsterdam, 1992, pp. 137-142, for strictly convex optimization problems, is extended to handle linear programming problems. Line search versions of both the DASA and the LPDASA are given.
Stochastic dynamic programming has been extensively used in the optimization of long term hydrothermal scheduling problems due to its ability to cope with the nonlinear and stochastic characteristics of such problems,...
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Stochastic dynamic programming has been extensively used in the optimization of long term hydrothermal scheduling problems due to its ability to cope with the nonlinear and stochastic characteristics of such problems, and the fact that it provides a closed-loop feedback control policy. Its computational requirements, however, tend to be heavy even for systems with a small number of hydroplants, requiring some sort of modeling manipulation in order to be able to handle real systems. An alternative to closed-loop optimization is an approach that combines a deterministic optimization model with an inflow forecasting model in a partial open-loop feedback control framework. At each stage in this control policy, a forecast of the inflows during the period of planning is made, and an operational decision for the following stage is obtained by a deterministic optimization model. The present paper compares such closed-loop and partial open-loop feedback control policies in long term hydrothermal scheduling, using a single hydroplant system as a case study to focus the comparison on the feedback control performance. The comparison is made by simulation using data from historical and synthetical inflow sequences in the consideration of three different Brazilian hydroplants located in different river basins. Results have demonstrated that the performance of the partial open-loop feedback control policy is similar to that of the closed-loop control policy, and is even superior in dry streamflow periods.
This paper addresses the problem of global optimization by means of a monotonic transformation. With an observation on global optimality of functions under such a transformation, we show that a simple and effective al...
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This paper addresses the problem of global optimization by means of a monotonic transformation. With an observation on global optimality of functions under such a transformation, we show that a simple and effective algorithm can be derived to search within possible regions containing the global optima. Numerical experiments are performed to compare this algorithm with one that does not incorporate transformed information using several benchmark problems. These results are also compared to best known global search algorithms in the literature. In addition, the algorithm is shown to be useful for several neural network learning problems, which possess much larger parameter spaces.
The density dependence of the binary parameters of the Peng-Robinson equation of state in near the critical region was examined. Published solubility data of eight compounds in pure CO2 have been fitted to the Peng-Ro...
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The density dependence of the binary parameters of the Peng-Robinson equation of state in near the critical region was examined. Published solubility data of eight compounds in pure CO2 have been fitted to the Peng-Robinson equation in combination with one and two parameters van der Waals mixing rules and in combination with the three parameter density dependent mixing rule of Mohamed and Holder. A systematic study has been done to determine the influence of different terms in the mixing rules. In order to obtain density dependence, binary parameters were calculated for each isotherm at particular experimental point separately in the way to equalise experimental and calculated solubility data. The system was formulated as an equation-oriented model and solved by means of a nonlinear programming optimisation algorithm. For all compounds the binary interaction parameters thus obtained were found to vary strongly with pressure in the range from 75 bar to approximately 150 bar, i.e. near the critical end point (CEP) of the low temperature branch of the three phase solid-liquid-gas (SLG) curve. At higher pressures, the parameter is practically independent on pressure. In general, for the systems investigated, k(ij) increases linearly with increasing density and reaches a constant value at higher densities in the range from 700 to 800 kg/m(3), depending on the system under investigation. (C) 2002 Elsevier Science B.V. All rights reserved.
In the design of a chemical process (CP), certain design specifications (for example those related to process economics, process performance, safety, and the environment) must be satisfied. During the operation of the...
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In the design of a chemical process (CP), certain design specifications (for example those related to process economics, process performance, safety, and the environment) must be satisfied. During the operation of the plant. since design models have uncertainties associated with them, we need to ensure the flexibility of the CP. This means that within the region of uncertainty, all design specifications must be satisfied. In recent years, research has focused on the development of methods for flexibility analysis of the CP. There are three main sub-problems associated with flexibility analysis, namely evaluation of CP flexibility, evaluation of CP structural flexibility and determination of the optimal regime over which the flexibility of the CP is guaranteed. We have developed a general approach to solving the sub-problems based on the split and bound strategy.
This paper presents a nonlinear integer programming approach to the optimization phase of the yield management problem, which allows the imposition of constraints on the proportions of fare classes either in absolute ...
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This paper presents a nonlinear integer programming approach to the optimization phase of the yield management problem, which allows the imposition of constraints on the proportions of fare classes either in absolute terms or in relation to each other. Computational experience with the implementation of this approach is described, and some examples of the areas of applicability are discussed.
Augmented Lagrangian-SQP methods using Lipschitz-continuous Lagrange multiplier updates are analyzed. Kantorovich-style convergence results are proved and applied to the discretization of optimal control problems. The...
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Augmented Lagrangian-SQP methods using Lipschitz-continuous Lagrange multiplier updates are analyzed. Kantorovich-style convergence results are proved and applied to the discretization of optimal control problems. The existence of stationary points for the discretized problems is also discussed.
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