An optimising design method is presented for designing closed grinding circuits to meet the requirements for the particulate product expressed as a combination of the mean value and standard deviation of the particle ...
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An optimising design method is presented for designing closed grinding circuits to meet the requirements for the particulate product expressed as a combination of the mean value and standard deviation of the particle size. The grinding circuit is modelled by a discrete mathematical model describing the axial mixing and breakage of particles in the mill and a possible time delay in the recycle line. The design problem is formulated as a nonlinear programming task in which the convective flow velocity and the axial dispersion coefficient of the ground material are selected as design variables. The method proved to be a useful tool for optimising design of grinding systems, and can be applied as a decision aid for process engineers to improve the efficiency of processes and maintaining the quality required for the particular products. (C) 2004 Elsevier B.V. All rights reserved.
Equilibrium equations in the form of complementarity conditions often appear as constraints in optimization problems. Problems of this type are commonly referred to as mathematical programs with complementarity constr...
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Equilibrium equations in the form of complementarity conditions often appear as constraints in optimization problems. Problems of this type are commonly referred to as mathematical programs with complementarity constraints (MPCCs). A popular method for solving MPCCs is the penalty interior-point algorithm (PIPA). This paper presents an example for which PIPA converges to a nonstationary point, providing a counterexample to the established theory. The reasons for this adverse behavior are discussed.
This paper provides an introductory survey of a class of optimization problems known as bilevel programming. We motivate this class through a simple application, and then proceed with the general formulation of bileve...
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This paper presents a game-theoretic method for analyzing the security of computer networks. We view the interactions between an attacker and the administrator as a two-player stochastic game and construct a model for...
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We describe four approaches to solving nonconvex global optimization problems by convex nonlinear programming methods. It is assumed that the problem becomes convex when selected variables are fixed. The selected vari...
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ISBN:
(纸本)354026003X
We describe four approaches to solving nonconvex global optimization problems by convex nonlinear programming methods. It is assumed that the problem becomes convex when selected variables are fixed. The selected variables must be discrete, or else discretized if they are continuous. We first survey some existing methods: disjunctive programming with convex relaxations, logic-based outer approximation, and logic-based Benders decomposition. We then introduce a branch-and-bound method with convex quasi-relaxations (BBCQ) that can be effective when the discrete variables take a large number of real values. The BBCQ method generalizes work of Bollapragada, Ghattas and Hooker on structural design problems. It applies when the constraint functions are concave in the discrete variables and have a weak homogeneity property in the continuous variables.
This paper relates the experience of use of the optimal power flow software IPSO (Integrated Power System Optimizer) for solving problems related to the Belgian power system short term operation and planning. The opti...
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ISBN:
(纸本)0780391918
This paper relates the experience of use of the optimal power flow software IPSO (Integrated Power System Optimizer) for solving problems related to the Belgian power system short term operation and planning. The optimization is performed using the KNITRO solver based on an interior point algorithm. After a short description of the main algorithm features, the paper focuses on the utilisation of OPF program to solve two main optimization problems typical of the operation of the Belgian grid system that is highly interconnected to the UCTE grid: a/ the evaluation of the steady state TTC (Total Transfer Capability) which is a key component of the ATC (Available transfer capability) provided to the market operators and the quantification of the TRM (Transfer Reliability Margin) b/ the supervision of the Tertiary Voltage Control (TVC) that implements the maximization of the units individual reactive power margin through the emulation of the highly customized linear programming algorithm implemented within the EMS software for operational or planning purposes.
This paper presents a new sequential method for constrained nonlinear optimization problems. The principal characteristics of these problems are very time consuming function evaluations and the absence of derivative i...
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This paper presents a new sequential method for constrained nonlinear optimization problems. The principal characteristics of these problems are very time consuming function evaluations and the absence of derivative information. Such problems are common in design optimization, where time consuming function evaluations are carried out by simulation tools (e.g., FEM, CFD). Classical optimization methods, based on derivatives, are not applicable because often derivative information is not available and is too expensive to approximate through finite differencing. The algorithm first creates an experimental design. In the design points the underlying functions are evaluated. Local linear approximations of the real model are obtained with help of weighted regression techniques. The approximating model is then optimized within a trust region to find the best feasible objective improving point. This trust region moves along the most promising direction, which is determined on the basis of the evaluated objective values and constraint violations combined in a filter criterion. If the geometry of the points that determine the local approximations becomes bad, i.e. the points are located in such a way that they result in a bad approximation of the actual model, then we evaluate a geometry improving instead of an objective improving point. In each iteration a new local linear approximation is built, and either a new point is evaluated (objective or geometry improving) or the trust region is decreased. Convergence of the algorithm is guided by the size of this trust region. The focus of the approach is on getting good solutions with a limited number of function evaluations. (C) 2003 Elsevier B.V. All rights reserved.
This paper proposes a fast approach to generate length-preserved natural boundary for intrinsic parameterization. Given a triangular mesh with disk-like topology, we compute an optimal boundary for its parameterizatio...
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ISBN:
(纸本)0769524737
This paper proposes a fast approach to generate length-preserved natural boundary for intrinsic parameterization. Given a triangular mesh with disk-like topology, we compute an optimal boundary for its parameterization. An optimal boundary is expected to be length-preserved with the length of every triangular edge on the boundary is invariant before and after parameterization;also, the boundary is requested to be natural where the inner angle is close to the angle excess at every boundary vertex on the given mesh. Computation of a length-preserved natural boundary is formulated as a constrained non-linear optimization problem, the procedure of solving which is in general very time-consuming. Here, we speed tip the optimization by adopting the scheme of sequential linearly constrained programming. It is shown at the end of this paper that our length-preserved natural boundary could greatly improve the speed and quality of the original intrinsic parameterization.
It is important to design and operate energy conversion systems such as gas turbine cogeneration ones optimally from the thermoeconomic viewpoint. However, an energy conversion system has a complex network structure, ...
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ISBN:
(纸本)0791847276
It is important to design and operate energy conversion systems such as gas turbine cogeneration ones optimally from the thermoeconomic viewpoint. However, an energy conversion system has a complex network structure, and it takes much time to create its model for the thermoeconomic analysis and optimization. In this paper, a systems approach is presented for the performance analysis and optimization of mechanical systems with network structures, and it is applied to the thermoeconomic analysis and optimization of a gas turbine cogeneration unit. The system modeling for the performance analysis is conducted by a building block approach. Static and dynamic problems for the performance analysis are formulated as sets of nonlinear algebraic and differential algebraic equations, and arc solved by the Newton-Raphson method and a hierarchical combination of the Runge-Kutta and Newton-Raphson methods, respectively. The performance optimization is conducted to determine design and operation conditions which optimize performance criteria. This problem is formulated as a nonlinear programming one and is solved by a global optimization method. In the application, the cycle analysis is conducted to determine mass flow rates, pressures, and temperatures, which is followed by the exergy and cost analyses to determine exergy flow rates and efficiencies, and capital costs, respectively. In addition, design and operation conditions are determined to maximize the exergy efficiency or minimize the annual total cost based on the results of the cycle, exergy, and cost analyses. Through a numerical study, it turns out that the proposed systems approach enables one to conduct the thermoeconomic analysis and optimization efficiently.
The container loading problem has important industrial and commercial applications. An increase in the number of items in a container leads to a decrease in cost. For this reason the related optimization problem is of...
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The container loading problem has important industrial and commercial applications. An increase in the number of items in a container leads to a decrease in cost. For this reason the related optimization problem is of economic importance. In this work, a procedure based on a nonlinear decision problem to solve the cylinder packing problem with identical diameters is presented. This formulation is based on the fact that the centers of the cylinders have to be inside the rectangular box defined by the base of the container (a radius far from the frontier) and far from each other at least one diameter. With this basic premise the procedure tries to find the maximum number of cylinder centers that satisfy these restrictions. The continuous nature of the problem is one of the reasons that motivated this study. A comparative study with other methods of the literature is presented and better results are achieved. (C) 2003 Elsevier B.V. All rights reserved.
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