Abstract
In this article is proposed a simple method for estimating or characterize the behaviour of complex systems, in particular when these are being studied throughout simulation. Usual ways of treating the complex output data obtained from the activity (real or simulated) of such a kind of systems, which in many cases people classify and analyse along the time domain, usually the most complex perspective, is herein substituted by the idea of representing such data in the frequency domain, somehow like what is commonly done in Fourier Analysis and in Quantum Mechanics. This is expected to give the analyst a more holistic perspective on the system's behaviour, as well as letting him/her choose almost freely the complex states in which such behaviour is to be projected. We hope this will lead to simpler processes in characterizing complex systems.

Abstract
In this paper will be compared, by means of a next event dynamic simulation, two different stock refill policies applied to the same in-lined one-product Supply Chain. The first method is the Japanese method usually known as KANBAN(1) (similar to the "Two Bins" method, in terms of dynamics), and the second is a naive method named by the authors the "BanKan" for the reasons that will be explained later in this text. The surprising results obtained show an obvious operational advantage of the naive method, at least under the conditions of the present Supply Chain design and configuration. This method does not make use of any criteria dependent on the actual stock level at the facility, and it was also observed that the materials flow through the Supply Chain as in a "river without dams", and with extremely low local inventory, as it was defended by Taiichi Ohno, the father of just-in-time (JIT) systems, in the 1980s.

Abstract
The nature of warehouse design requires the manipulation of large amounts of data and is often an iterative process that forces the designer to go through the different design phases several times before reaching the final solution. This suggests an integrated computer environment that can give support to the user during all the design phases. The need for a flexible tool, easier to use, lead to the development of a Decision Support System: AWARD (Advanced WARehouse Design). This paper presents further developments of the DSS and shows a successful example of application of the new functionalities: a simulation model of a full automated warehouse developed for EFACEC, a large Portuguese company in the warehouse design, building and consultancy business.

Abstract
A simulation model of a full automated warehouse was custom developed for EFACEC, a large Portuguese company in the warehouse design, building and consultancy business. EFACEC was preparing a proposal for a client and they needed the model to evaluate and test their options. They also wanted to use the model as a marketing tool to gain the contract. Two persons with previous experience in simulation formed the development team. The model was developed in four months with full time dedication, but was inflexible to support significant changes after EFACEC won the bid. Furthermore, the increasing demand for warehouse design made the development of specific hard coded simulation models for EFACEC inadequate. The need for a flexible tool, easier to use, lead to the development of a Decision Support System: AWARD (Advanced WARehouse Design).

Abstract
Data in this article results from a study of simulation about the procurement of addictives for lubricants in the Oil Refinery of Porto (Portugal). Here we describe the real case under study as well as the method we have chosen to board it by means of simulation, which finally leaded us to some interesting results regarding the choices on purchasing the addictives from the suppliers. Costs including transportation, holding and stockouts have been considered during the simulation as well as in the final conclusions, which let us recommend a more frequent reordering of materials at the lubricants plant. This we expect to result in the saving of around 0.3MEURO/year in global costs.

Abstract
This paper presents some lines of thinking related with the establishment of a concrete mathematical basis to measure the ability of enterprises in a supply chain to maintain equilibrium under unexpected variations. It will be argued that flexibility will be the most appropriate term to classify the concept behind such idea and that agility can be understood as a special case of flexibility. Then, a simple theory of flexibility directed to demand variations in the supply chain is deduced and commented, as well as some results achieved by dynamic supply chain simulation presented and discussed.