Abstract
The phenomenon of the enterprise organizational reconfiguration and its dynamics as a business alignment enabler is discussed. Business alignment means the enterprise's actions undertaken to gain synergy between the business; that is, the market opportunity and the provision of the required, or innovative, product, with the required, or designed, specifications at the required, or proper, time, with the lowest cost and best possible return (financial or other). The enterprise's organization "fast reconfiguration," either as a proactive or as a reactive action, or "fast adaptation" or "flexibility" (as a "reactive" action), is seen as the main enabler of business alignment and the main requirement for achieving competitiveness. The need to keep a close alignment with the dynamic market environment in permanent change implies the high dynamics of the organizations' organization, or organizational structure, reconfiguration. The first part of the text presents enterprise's requirements for competitiveness and business alignment, while the second part discusses the phenomenon of the enterprise reconfigurability as the business alignment enabler. In the third part, an analysis of some organizational and management approaches, from the reconfigurability point of view, is presented. The text ends with a conclusion and references. © 2007, Idea Group Inc.

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The process of resources systems selection takes an important part in Agile/Virtual Enterprises (A/V E) integration. However, the resources systems selection is a difficult matter to solve in A/VE because: it can be of exponential complexity resolution; it can be a multi criteria problem; and because there are different types of A/V Es with different requisites that have originated the creation of a specific resources selection model for each one of them. In our A/V E project we have made some progress in this matter and identified the principal gaps to be solved. This paper will show one of those gaps in the algorithms area to be applied to the problem. In attention to that gaps we address the necessity to develop new algorithms and with more information disposal, for its selection by the Broker. In this paper we propose a genetic algorithm to deal with a specific case of resources system selection problem when the space solution dimension is high.