Um modelo de otimização inteira mista e heurísticas relax and fix para a programação da produção de fábricas de refrigerantes de pequeno porte

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Primal-dual logarithmic barrier and augmented Lagrangian function to the loss minimization in power systems

This article presents a new approach to minimize the losses in electrical power systems. This approach considers the application of the primal-dual logarithmic barrier method to voltage magnitude and tap-changing transformer variables, and the other inequality constraints are treated by augmented Lagrangian method. The Lagrangian function aggregates all the constraints. The first-order necessary conditions are reached by Newton's method, and by updating the dual variables and penalty factors. Test results are presented to show the good performance of this approach.

Logarithmic barrier-augmented Lagrangian function to the optimal power flow problem

This paper presents a new approach to solve the Optimal Power Flow problem. This approach considers the application of logarithmic barrier method to voltage magnitude and tap-changing transformer variables and the other constraints are treated by augmented Lagrangian method. Numerical test results are presented, showing the effective performance of this algorithm. (C) 2005 Elsevier Ltd. All rights reserved.

STOCHASTIC QUANTIZATION AND 1/N EXPANSION

We study the 1/N expansion of field theories in the stochastic quantization method of Parisi and Wu using the supersymmetric functional approach. This formulation provides a systematic procedure to implement the 1/N expansion which resembles the ones used in the equilibrium. The 1/N perturbation theory for the nonlinear sigma-model in two dimensions is worked out as an example.

A heuristic method for reactive power planning

An approach for solving reactive power planning problems is presented, which is based on binary search techniques and the use of a special heuristic to obtain a discrete solution. Two versions were developed, one to run on conventional (sequential) computers and the other to run on a distributed memory (hypercube) machine. This latter parallel processing version employs an asynchronous programming model. Once the set of candidate buses has been defined, the program gives the location and size of the reactive sources needed(if any) in keeping with operating and security constraints.

Nonsmooth continuous-time optimization problems: Necessary conditions

We consider Lipschitz continuous-time nonlinear optimization problems and provide first-order necessary optimality conditions of both Fritz John and Karush-Kuhn-Tucker types. (C) 2001 Elsevier B.V. Ltd. All rights reserved.

The application of preprocessing and cutting plane techniques for a class of production planning problems

This paper investigates properties of integer programming models for a class of production planning problems. The models are developed within a decision support system to advise a sales team of the products on which to focus their efforts in gaining new orders in the short term. The products generally require processing on several manufacturing cells and involve precedence relationships. The cells are already (partially) committed with products for stock and to satisfy existing orders and therefore only the residual capacities of each cell in each time period of the planning horizon are considered. The determination of production recommendations to the sales team that make use of residual capacities is a nontrivial optimization problem. Solving such models is computationally demanding and techniques for speeding up solution times are highly desirable. An integer programming model is developed and various preprocessing techniques are investigated and evaluated. In addition, a number of cutting plane approaches have been applied. The performance of these approaches which are both general and application specific is examined.

Solution approaches for the soft drink integrated production lot sizing and scheduling problem

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Optimized Allocation of Control and Protective Devices in Electric Distribution Systems

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Dissipative three-wave structures in stimulated backscattering. I. A subluminous solitary attractor

We present a solitary solution of the three-wave nonlinear partial differential equation (PDE) model - governing resonant space-time stimulated Brillouin or Raman backscattering - in the presence of a cw pump and dissipative material and Stokes waves. The study is motivated by pulse formation in optical fiber experiments. As a result of the instability any initial bounded Stokes signal is amplified and evolves to a subluminous backscattered Stokes pulse whose shape and velocity are uniquely determined by the damping coefficients and the cw-pump level. This asymptotically stable solitary three-wave structure is an attractor for any initial conditions in a compact support, in contrast to the known superluminous dissipative soliton solution which calls for an unbounded support. The linear asymptotic theory based on the Kolmogorov-Petrovskii-Piskunov assertion allows us to determine analytically the wave-front slope and the subluminous velocity, which are in remarkable agreement with the numerical computation of the nonlinear PDE model when the dynamics attains the asymptotic steady regime. © 1997 The American Physical Society.

Analog nonderivative optimizers

Analog networks for solving convex nonlinear unconstrained programming problems without using gradient information of the objective function are proposed. The one-dimensional net can be used as a building block in multi-dimensional networks for optimizing objective functions of several variables.

A new solution to the optimal power flow problem

A new approach to solving the Optimal Power Flow problem is described, making use of some recent findings, especially in the area of primal-dual methods for complex programming. In this approach, equality constraints are handled by Newton's method inequality constraints for voltage and transformer taps by the logarithmic barrier method and the other inequality constraints by the augmented Lagrangian method. Numerical test results are presented, showing the effective performance of this algorithm. © 2001 IEEE.

Modified barrier method for optimal power flow problem

In this paper is presented a new approach for optimal power flow problem. This approach is based on the modified barrier function and the primal-dual logarithmic barrier method. A Lagrangian function is associated with the modified problem. The first-order necessary conditions for optimality are fulfilled by Newton's method, and by updating the barrier terms. The effectiveness of the proposed approach has been examined by solving the Brazilian 53-bus, IEEE118-bus and IEEE162-bus systems.

A constructive heuristic algorithm to Short Term Transmission Network Expansion Planning

In this paper a method for solving the Short Term Transmission Network Expansion Planning (STTNEP) problem is presented. The STTNEP is a very complex mixed integer nonlinear programming problem that presents a combinatorial explosion in the search space. In this work we present a constructive heuristic algorithm to find a solution of the STTNEP of excellent quality. In each step of the algorithm a sensitivity index is used to add a circuit (transmission line or transformer) to the system. This sensitivity index is obtained solving the STTNEP problem considering as a continuous variable the number of circuits to be added (relaxed problem). The relaxed problem is a large and complex nonlinear programming and was solved through an interior points method that uses a combination of the multiple predictor corrector and multiple centrality corrections methods, both belonging to the family of higher order interior points method (HOIPM). Tests were carried out using a modified Carver system and the results presented show the good performance of both the constructive heuristic algorithm to solve the STTNEP problem and the HOIPM used in each step.

Planning of secondary distribution circuits through evolutionary algorithms

In this work, the planning of secondary distribution circuits is approached as a mixed integer nonlinear programming problem (MINLP). In order to solve this problem, a dedicated evolutionary algorithm (EA) is proposed. This algorithm uses a codification scheme, genetic operators, and control parameters, projected and managed to consider the specific characteristics of the secondary network planning. The codification scheme maps the possible solutions that satisfy the requirements in order to obtain an effective and low-cost projected system-the conductors' adequate dimensioning, load balancing among phases, and the transformer placed at the center of the secondary system loads. An effective algorithm for three-phase power flow is used as an auxiliary methodology of the EA for the calculation of the fitness function proposed for solutions of each topology. Results for two secondary distribution circuits are presented, whereas one presents radial topology and the other a weakly meshed topology. © 2005 IEEE.