Interaction Balance Principle Research Articles

Interaction balance optimization in multidisciplinary design optimization problems

As a bi-level optimization method, collaborative optimization can solve multidisciplinary design optimization problems in practical engineering effectively. However, if there are high-dimensional couplings in a multidisciplinary design optimization problem, a large number of compatibility constraints will be required in collaborative optimization. In this situation, collaborative optimization will not be suitable to be utilized because of low computational efficiency or divergence issue. To solve this problem, an efficient interaction balance optimization method is proposed in this article. In interaction balance optimization method, the simple coordination strategy of interaction balance principle and the distributed optimization strategy of collaborative optimization can be integrated effectively. Lagrange multipliers are used instead of compatibility constraints to maintain the consistency between any two coupled disciplines. Two examples are given to show the effectiveness of the proposed method.

Towards autonomic performance management of large scale data centers using interaction balance principle

In this paper, an autonomic performance management approach is introduced that can be applied to a general class of web services deployed in large scale distributed environment. The proposed approach utilizes traditional large scale control-based algorithms by using interaction balance approach in web service environment for managing the response time and the system level power consumption. This approach is developed in a generic fashion that makes it suitable for web service deployments, where web service performance can be adjusted by using a finite set of control inputs. This approach maintains the service level agreements, maximizes the revenue, and minimizes the infrastructure operating cost. Additionally, the proposed approach is fault-tolerant with respect to the failures of the computing nodes inside the distributed deployment. Moreover, the computational overhead of the proposed approach can also be managed by using appropriate value of configuration parameters during its deployment.

Search for organising principles: understanding in systems biology

Due in large measure to the explosive progress in molecular biology, biology has become arguably the most exciting scientific field. The first half of the 21st century is sometimes referred to as the 'era of biology', analogous to the first half of the 20th century, which was considered to be the 'era of physics'. Yet, biology is facing a crisis--or is it an opportunity--reminiscent of the state of biology in pre-double-helix time. The principal challenge facing systems biology is complexity. According to Hood, 'Systems biology defines and analyses the interrelationships of all of the elements in a functioning system in order to understand how the system works.' With 30000+ genes in the human genome the study of all relationships simultaneously becomes a formidably complex problem. Hanahan and Weinberg raised the question as to whether progress will consist of 'adding further layers of complexity to a scientific literature that is already complex almost beyond measure' or whether the progress will lead to a 'science with a conceptual structure and logical coherence that rivals that of chemistry or physics.' At the core of the challenge is the need for a new approach, a shift from reductionism to a holistic perspective. However, more than just a pronouncement of a new approach is needed. We suggest that what is needed is to provide a conceptual framework for systems biology research. We propose that the concept of a complex system, i.e. a system of systems as defined in mathematical general systems theory (MGST), is central to provide such a framework. We further argue that for a deeper understanding in systems biology investigations should go beyond building numerical mathematical or computer models--important as they are. Biological phenomena cannot be predicted with the level of numerical precision as in classical physics. Explanations in terms of how the categories of systems are organised to function in ever changing conditions are more revealing. Non-numerical mathematical tools are appropriate for the task. Such a categorical perspective led us to propose that the core of understanding in systems biology depends on the search for organising principles rather than solely on construction of predictive descriptions (i.e. models) that exactly outline the evolution of systems in space and time. The search for organising principles requires an identification/discovery of new concepts and hypotheses. Some of them, such as coordination motifs for transcriptional regulatory networks and bounded autonomy of levccels in a hierarchy, are outlined in this article. Experimental designs are outlined to help verify the applicability of the interaction balance principle of coordination to transcriptional and posttranscriptional networks.

A parallel processing algorithm for co-ordination of directional overcurrent relays in interconnected power systems

The problem of coordinating the setting of directional overcurrent relays in an interconnected power system is considered. The power system is decomposed into subsystems to give a constraint matrix of a diagonal structure with linking variables. Each subsystem is solved using the sparse dual revised simplex algorithm of linear programming. Benders algorithm for linear programming may be used to coordinate the solution from each subsystem and the master system. The authors propose a new parallel processing algorithm for this coordination procedure which depends on the interaction balance principle of linear programming. This algorithm has been applied to various size systems and the results compared with those obtained using a conventional linear programming algorithm and Benders algorithm. It is shown that the proposed algorithm is more computationally efficient than previous methods.

Hierarchically Optimal Distribution Algorithm of Large Water Supply Systems

This paper presents the mathematical model of the optimal distribution problem for large uroan water supply systems. A two-level hierarchically optimal distrioutiun algoritnm to solve this problem is proposed by means of the interaction balance principle in large scale systems theory. Based on Kuhn-Tucker's optimality necessary conditions, an iterative calculation method to solve subproblems is also discussed. The proposed algorithm nas been simulated of microcomputer, and the results are satisfactory. It will oe put into operation in a computer distribution system of a real uroan Water supply system in the near future.

A Hierarchical Strategy for Traffic Control in Urban Networks

The paper presents an application of hierarchical multi level system theory in network traffic control problem solving. Street network is represented by a directed graph. Nodes represent signalized intersections, and arcs represent street sections between adjacent signal ized intersections. Traffic process is described by delay-difference-of-offset functions. Loop constraints on offsets are incorporated in the model. The problem is to minimize loses (delay) in the network. Two-level hierarchical system structure is used in solving the problem. For subproblems coordination interaction balance principle is applied. It is shown that tasks performed by first and second level subsystems are quite simple, and suitable for real time control.

On-line co-ordination under uncertainty of weakly interacting dynamical systems

The problem of on-line co-ordination of a hierarchically controlled dynamical system under uncertainty by using the interaction balance principle is discussed. For the sake of simplicity, a two-level system consisting of two subsystems interconnected by means of buffer storages is considered. In order to avoid measure theoretic difficulties, only a finite set of typical disturbance realizations are taken to represent the uncertainty in the system. The uncertainty leads to a co-ordination method based on a ‘balance in the mean’ condition. It turns out that the weakness of the mutual interaction between the subsystems is an important concept. In the case considered the buffer storages contribute to the weakness of the interaction to a noticeable degree.

On the On-Line Coordination Under Uncertainty of Hierarchically Controlled Dynamical Systems Containing Buffer Storages

The problem of on-line coordination of a hierarchically controlled dynamical system under uncertainty by using the interaction balance principle is discussed. For the sake of simplicity, a two-level system consisting of two subsystems interconnected by means of buffer storages is considered. The uncertainty leads to a coordination method based on a “balance in the mean” condition. It turns out that the weakness of the coupling between the subsystems is an important concept. In the case considered the buffer storages contribute to the weakness of this coupling to a noticeable degree.

A Multi-Level Approach to Steady State Control of a Multi-Product, Multi-Factor Firm

The problem considered here is that of steady state optimization of a multi-product, multi-factor firm, composed of a number of interconnected complex multi-product, multi-factor production subunits under conditions of imperfectly competitive market. The objective function is assumed to be nonlinear and partially nonseparable profit function of a firm, and the problem of optimization is considered under both equality and nonequality type constraints. Difficulties of high dimensionality are alleviated by use of decomposition technique and interaction balance principle. The overall optimization problem is decomposed and two-level control structure with local decision subunits in the first level and coordination subunit on the second level obtained. Conditions for coordinability of a decomposed system by use of interaction balance principle and necessary and sufficient conditions for optimality of local optimization subproblems are given. The structure of coordination subunit for different types of total profit function and different types of interconnections between production subunits is discussed as well as the nature of coordination parameters. A numerical example is presented as an illustration of coordination procedure.

Two coordination principles and their application in large scale systems control

Two principles for coordinating the controllers of interacting subprocesses are postulated in order to provide guidance in synthesizing structures for multi-level, or hierarchial, control systems. One principle is based on interaction prediction and the other on interaction balance. Both are formulated in the general systems theoretic framework for the case in which the subprocess and overall process control objectives are optimization. The principles are however extendable to other control objectives. Sufficient conditions for the successful application of the interaction balance principle are given for the case when the sub-processes and overall process are defined on normed linear spaces. Some examples are given to illustrate the required conditions.