General Network Structure Research Articles

Planning Hydro and Biomass Electric Energy Coproduction

Coordination of hydro and biomass electric energy production is achieved with two hierarchically coupled problems. The first problem concerns long-term strategies for the hydroelectric system and forest development, settling control actions that allows to obtain a target yearly biomass output. The other problem schedules hydroelectric and biomass-powered plants to meet loads over a midterm horizon, while minimizing the use of either hydro or biomass resources. Special emphasis is put on the solution of the mid-term problem. A generalized network structure for the problem is disclosed and exploited with a specially tailored optimization engine.

Network decomposition of general financial equilibria with transaction costs

In this paper, we developed a new general financial equilibrium model with transaction costs which considers multiple sectors of an economy, each of which seeks to determine its optimal composition of instruments held as assets and as liabilities in its portfolio. The governing equilibrium conditions are shown to satisfy a variational inequality problem, which is then studied in terms of existence and other qualitative properties. A decomposition algorithm is proposed which exploits the underlying generalized network structure of the problem and convergence results obtained. Finally, the algorithm is applied to compute the equilibrium asset, liability, and price pattern in several numerical examples. © 1996 John Wiley & Sons, Inc.

Criteria to evaluate approximate belief network representations in expert systems

The representation of uncertainty, and reasoning in the presence of uncertainty, has become an important area of research in expert systems. Belief networks have been found to provide an effective framework for the representation of uncertainty using probability calculus. Unfortunately, belief propagation techniques for general network structures are computationally intense. In this paper, we present belief network representations that approximate the underlying dependency structure in a problem domain in order to allow efficient propagation of beliefs. An important issue then is one of obtaining the ‘best’ approximate representation. A criterion is required to measure the closeness of the approximate to the actual. We examine desirable features of measures that compare approximate representations to the actual one. We identify two well-known measures, called the logarithm rule and the quadratic rule, as having special properties for evaluating approximations. We present a new result that shows the equivalence of using the logarithm rule to that of finding the maximum likelihood estimator. Next, we discuss the modeling implications of using the logarithm rule and the quadratic rule in terms of the nature of solutions that are obtained, and the computational effort required to obtain such solutions. Finally, we use a decision theoretic approach to compare such solutions using a common frame of reference. A simple decision problem is modelled as a belief network, and the comparison is performed over a wide range of probability distributions and cost functions. Our results suggest that the logarithm rule is very appropriate for evaluating approximate representations.

A subgradient-based optimization for reservoirs system management

The problem of determining the optimal operating policy for a system of reservoirs equipped with hydroelectric power plants is a nonlinear programming problem. In general, practitioners have found it hard to solve even a problem for a system with a small number of planning periods and hydroelectric plants using current nonlinear programming techniques. This is due, in large measure, to complex nonlinearities of the power generating functions and a large number of linear equality constraints involved in the model. Furthermore, most reservoirs systems in arid regions have periods of low water level which often results in an empty feasible region adding considerable difficulties to the operational feasibilities of the solutions. In this paper, we provide a general formulation of the water resource allocation problem with explicit engineering details generally omitted or oversimplified in the published literature, and investigate several solution procedures for their applicabilities, and we develop an efficient algorithmic framework exploiting the general water resource system special network structure to solve the linear equality constraints. Practical feasibility of this approach is demonstrated in several applications with a real water resource system.

Locally recurrent globally feedforward networks: a critical review of architectures

In this paper, we will consider a number of local-recurrent-global-feedforward (LRGF) networks that have been introduced by a number of research groups in the past few years. We first analyze the various architectures, with a view to highlighting their differences. Then we introduce a general LRGF network structure that includes most of the network architectures that have been proposed to date. Finally we will indicate some open issues concerning these types of networks.

A heuristic for finding embedded network structure in mathematical programmes

An intuitive description is given of how to recognise when a mathematical programme can be converted to a network flow problem. In practice, it is more likely that a mathematical programme with a high degree of network structure will have additional complicating constraints. Thus, a heuristic is presented for identifying a maximal subset of the constraints which can be converted to a network flow problem. Computational results show that the heuristic is highly effective, and that much larger networks are identified by seeking a general network structure, rather than limiting the search to a subset of rows giving at most one +1 and one −1 in each column, as has been done previously.

On the Realization of a Kolmogorov Network

with Q 2 2N + 1 provides theoretical support for neural networks that implement multivariate mappings (Hecht-Nielson 1987; Lippmann 1987). Girosi and Poggio (1989) criticized Kolmogorov's theorem as irrelevant. They based their criticism mainly on the fact that the inner functions p,,. are highly nonsmooth and the output functions gq are not in a parameterized form. However, this criticism was not convincing: Kurkova (1991) argued that highly nonsmooth functions can be regarded as limits or sums of infinite series of smooth functions, and the problems in realizing a Kolmogorov network can be eliminated through approximately implementing (~4. and g, with known networks. In this note we present our view on the discussion from a more essential point of view. Since ( P, . in equation 0.1 should be universal, Kolmogorov's theorem can be regarded as a proof of a transformation of representation of multivariate functions in terms of the Q univariate output functions g,. [In some improved versions of Kolmogorov's theorem it is proved that only one g in equation 0.1 is necessary (Lorentz 19661.1 Such a strategy is embedded in the network structure as shown in Figure 1. (Note that the block T is independent off.) If Figure 1 is thought of as a general network structure for approximation of multivariate functions, a question is whether an arbitrarily given multivariate function f can be (approximately) implemented through an (approximate) implementation of the corresponding Q univariate functions g,. To this question we have an answer as stated below:

A decomposition method for optimization of large-system reliability

The authors consider a decomposition approach for optimization of the reliability of a large system with a general network structure. A three-level methodology is developed for optimal allocation of available resources among subsystems in order to ensure maximization of system reliability. The decentralized nature of this methodology greatly reduces the complexity of the large problem and facilitates seeking the optimal solution. Two examples show that the complexity of a large system can be greatly reduced by solving several smaller-dimensional subproblems iteratively. Subproblems whose dimensions are small can be efficiently solved by an existing nonlinear programming method. Another important feature of the approach is the possible simplification of the objective function during the solution. This leads in some cases to an analytic solution for the lower-level optimization problems in the three-level decomposition solution.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

Modeling of building evacuation problems by network flows with side constraints

In this paper we model building evacuations by network flows with side constraints. Side constraints come from variable arc capacities on some arcs which are functions of flows in incident arcs. In this context we study maximum flow, minimum cost, and minimax objectives. For some special structured networks we propose ‘greedy’ algorithms for solving these problems. For more general network structures, solution procedures are recommended which take advantage of the network structures of the problems.

Theory and application of semi-indefinite networks

A semi-indefinite network is any network in which the admittance matrix has only the row entries or only the column entries summing to zero. As a result of this property, the port currents of a semi-indefinite network form a dependent set given certain restrictions. Semi-indefinite networks are used in a general network structure for the simulation of floating immittances. A method is given for the transformation of networks which simulate grounded immittances to networks which simulate floating immittances.

Software reliability of programs with network structure

The aim of this paper is to present the reliability expression of programs/packages with general network structure, which is not sequential, branch or parallel in logic flow of the concerned algorithm. The reliability expression for logic flow ( R L ) of an example program of a general network structure (whose segments are listed in Appendix 1) is discussed and thereby overall reliability expression for the entire program which can be built in several different ways is derived. Such evaluations help increase the probability of programs having complex structure to be executed without errors on the computer system. The problem is obviously of great interest to programmers/system analysts while designing the flow system, debugging or testing the program.

DNA: The Digital Network Architecture

Recognizing the need to share resources and distribute computing among systems, computer manufacturers have been designing network components and communication subsystems as part of their hardware/software system offerings. A manufacturer's general purpose network structure must support a wide range of applications, topologies, and hardware configurations. The Digital Network Architecture (DNA), the architectural model for the DECnet family of network implementations, has been designed to meet these specific requirements and to create a communications environment among the heterogeneous computers comprising Digital's systems. This paper describes the Digital Network Architecture, including an overview of its goals and structure, and details on the interfaces and functions within that structure. The protocols implementing the functions of DNA are described, including the motivations for the specific designs, alternatives and tradeoffs, and lessons learned from the implementations. The protocol descriptions include discussions of addressing, error control, flow control, synchronization, flexibility, and performance. The paper concludes with examples of DECnet operation.

A general concept network structure for the production of index displays

Desirable characteristics of index displays are outlined; and a single underlying structure for a production of a variety of index displays is proposed, namely a network in which both concepts and links between concepts are represented by nodes, so that information about both may be stored using the same mechanisms. Algorithmic extraction of subnetworks for local or modular use is discussed, as well as possible approaches to structuring of index displays. Some details are given on implementation to date using a DEC system-10 COBOL ISAM database, and on experimentation with display generation.

Graph Models for Library Information Networks

The design and study of library information networks are enhanced by the use of the concepts which have been developed by graph theorists. In this paper we expand upon this theme, proposing a general network structure which we believe to be a good model for a wide variety of library and other information networks. The basic concepts from graph theory are illustrated with the aid of a hypothetical Public Library Access Network (PLAN).