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Arzola J. Sistemas de Ingeniería (Engineering Systems), Felix Varela Publishing House, Havana, 2000
Abstract
In the book the results obtained by the author until 1999 year in the elaboration of an Analysis and Synthesis metodology for the analysis and synthesis of engineering systems is presented. The exposition is completed with optimization and simulation methods, including metaheuristics and numerous appliclations examples firstly published.
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In this paper we further investigate the problem of finding nadir criterion values (minimum criterion values over the nondominated set) in multiple objective linear programming. Although easy to obtain, the minimum values present in a payoff table are unreliable and should only be used with caution, especially in problems that have more than a small number of extreme points. To obtain better estimates of the nadir criterion values without adding great complexity to the task, we present an approach based upon the use of reference directions. At each iteration of this approach, a reference direction is chosen that maximally minimizes the objective under consideration. We proceed with reference directions that accomplish this until the objective under consideration reaches a local minimum over the nondominated set. Then a cutting plane is inserted into the problem and another direction, if one can be found, that maximally minimizes the objective under consideration is employed. Although the method is heuristic, computational experience shows that much better estimates of the nadir criterion values can be obtained than from payoff tables.
A new method for finding the maximum of a general non-linear function of several variables within a constrained region is
described, and shown to be efficient compared with existing methods when the required optimum lies on one or more constraints.
The efficacy of using effective constraints to eliminate variables is demonstrated, and a program to achieve this easily and
automatically is described. Finally, the performance of the new method (the “Complex” method) with unconstrained problems,
is compared with those of the Simplex method, from which it was evolved, and Rosenbrock's method.
A three stage approach to the development of multi-agent systems is proposed involving functional decomposition, agent representation, and information flow integration. The information flow integration stage is discussed in detail. A rule-based agent integration for construction of autonomous subsystems and systems useful in integrated manufacturing is presented. The approach formalizes the integration process that a system analyst solves in an ad hoc manner. The approach presented facilitates the discovery of new integrated manufacturing solutions. It involves generation of a set of autonomous agents for building an overall system. Hierarchically structured subsystems are developed at different levels of abstraction that parallel the approach used by an expert system analyst. The implementation of an integration process in an object-oriented programming environment is also suggested.