980 resultados para transportation model


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The purposes of this report (Phase II of the project) are to specify in mathematical form the individual modules of the conceptual model developed in Phase I, to identify and evaluate sources of data for the model set, and to develop the transport networks necessary to support the models.

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A method for optimal transmission network expansion planning is presented. The transmission network is modelled as a transportation network. The problem is solved using hierarchical Benders decomposition in which the problem is decomposed into master and slave subproblems. The master subproblem models the investment decisions and is solved using a branch-and-bound algorithm. The slave subproblem models the network operation and is solved using a specialised linear program. Several alternative implementations of the branch-and-bound algorithm have been rested. Special characteristics of the transmission expansion problem have been taken into consideration in these implementations. The methods have been tested on various test systems available in the literature.

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The usefulness of the application of heuristic algorithms in the transportation model, first proposed by Garver, is analysed in relation to planning for the expansion of transmission systems. The formulation of the mathematical model and the solution techniques proposed in the specialised literature are analysed in detail. Starting with the constructive heuristic algorithm proposed by Garver, an extension is made to the problem of multistage planning for transmission systems. The quality of the solutions found by heuristic algorithms for the transportation model is analysed, as are applications in problems of planning transmission systems.

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Mode of access: Internet.

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A novel constructive heuristic algorithm to the network expansion planning problem is presented the basic idea comes from Garver's work applied to the transportation model, nevertheless the proposed algorithm is for the DC model. Tests results with most known systems in the literature are carried out to show the efficiency of the method.

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"HHP-25/11-83(2M)E"--P. [4] of cover.

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La optimización de sistemas y modelos se ha convertido en uno de los factores más importantes a la hora de buscar la mayor eficiencia de un proceso. Este concepto no es ajeno al transporte escolar, ambiente que cambia constantemente al ritmo de las necesidades de sus clientes, y que responde ante una fuerte responsabilidad frente a sus usuarios, los niños que hacen uso del servicio, en cuanto al cumplimiento de tiempos y seguridad, mientras busca constantemente la reducción de costos. Este proyecto expone las problemáticas presentadas en The English School en esta área y propone un modelo de optimización simple que permitirá notables mejoras en términos de tiempos y costos, de tal forma que genere beneficios para la institución en términos financieros y de satisfacción al cliente. Por medio de la implementación de este modelo será posible identificar errores comunes del proceso, se identificarán soluciones prácticas de fácil aplicación en el manejo del transporte y se presentarán los resultados obtenidos en la muestra utilizada para desarrollar el proyecto.

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This article presents a well-known interior point method (IPM) used to solve problems of linear programming that appear as sub-problems in the solution of the long-term transmission network expansion planning problem. The linear programming problem appears when the transportation model is used, and when there is the intention to solve the planning problem using a constructive heuristic algorithm (CHA), ora branch-and-bound algorithm. This paper shows the application of the IPM in a CHA. A good performance of the IPM was obtained, and then it can be used as tool inside algorithm, used to solve the planning problem. Illustrative tests are shown, using electrical systems known in the specialized literature. (C) 2005 Elsevier B.V. All rights reserved.

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A constructive heuristic algorithm to solve the transmission system expansion planning problem is proposed with the aim of circumventing some critical problems of classical heuristic algorithms that employ relaxed mathematical models to calculate a sensitivity index that guides the circuit additions. The proposed heuristic algorithm is in a branch-and-bound algorithm structure, which can be used with any planning model, such as Transportation model, DC model, AC model or Hybrid models. Tests of the proposed algorithm are presented on real Brazilian systems.

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An algorithm is presented that finds the optimal plan long-term transmission for till cases studied, including relatively large and complex networks. The knowledge of optimal plans is becoming more important in the emerging competitive environment, to which the correct economic signals have to be sent to all participants. The paper presents a new specialised branch-and-bound algorithm for transmission network expansion planning. Optimality is obtained at a cost, however: that is the use of a transportation model for representing the transmission network, in this model only the Kirchhoff current law is taken into account (the second law being relaxed). The expansion problem then becomes an integer linear program (ILP) which is solved by the proposed branch-and-bound method without any further approximations. To control combinatorial explosion the branch- and bound algorithm is specialised using specific knowledge about the problem for both the selection of candidate problems and the selection of the next variable to be used for branching. Special constraints are also used to reduce the gap between the optimal integer solution (ILP program) and the solution obtained by relaxing the integrality constraints (LP program). Tests have been performed with small, medium and large networks available in the literature.

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This work presents a branch-and-bound algorithm to solve the multi-stage transmission expansion planning problem. The well known transportation model is employed, nevertheless the algorithm can be extended to hybrid models or to more complex ones such as the DC model. Tests with a realistic power system were carried out in order to show the performance of the algorithm for the expansion plan executed for different time frames. © 2005 IEEE.

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This paper proposes a new strategy to reduce the combinatorial search space of a mixed integer linear programming (MILP) problem. The construction phase of greedy randomized adaptive search procedure (GRASP-CP) is employed to reduce the domain of the integer variables of the transportation model of the transmission expansion planning (TM-TEP) problem. This problem is a MILP and very difficult to solve specially for large scale systems. The branch and bound (BB) algorithm is used to solve the problem in both full and the reduced search space. The proposed method might be useful to reduce the search space of those kinds of MILP problems that a fast heuristic algorithm is available for finding local optimal solutions. The obtained results using some real test systems show the efficiency of the proposed method. © 2012 Springer-Verlag.

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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)