Abstract
In this paper, the Unit Commitment (UC) problem is presented and solved, following an innovative approach based on a metaheuristic procedure. The problem consists on deciding which electric generators must be committed, over a given planning horizon, and on defining the production levels that are required for each generator, so that load and spinning reserve requirements are verified, at minimum production costs. Due to its complexity, exact methods proved to be inefficient when real size problems were considered. Therefore, heuristic methods have for long been developed and, in recent years, metaheuristics have also been applied with some success to the problem. Methods like Simulated Annealing, Tabu Search and Evolutionary Programming can be found in several papers, presenting results that are sufficiently interesting to justify further research in the area. In this paper, a resolution framework based on GRASP - Greedy Randomized Adaptive Search Procedure - is presented. To obtain a general optimisation tool, capable of solving different problem variants and of including several objectives, the operations involved in the optimisation process do not consider any particular characteristics of the classical UC problem. Even so, when applied to instances with very particular structures, the computational results show the potential of this approach.

Abstract
This article presents the results of a qualitative study of a multi-channel bank. It aims at developing new methods of gathering user requirements for web interfaces, joining HCI and Marketing perspectives. The results obtained so far indicate that, as most of financial operations are functionally available in the different service channels, experience requirements become increasingly important. In this context, essential use cases are particularly valuable in improving the process of gathering customer requirements. As they allow the analysis of users' interaction needs in a channel-independent way, their use can improve decisions on what services are best suited to each channel, to effectively address customer needs across different interaction modes, and make an efficient allocation of resources among channels.

Abstract
The commercial use of the Internet for service provision has deeply changed the environment where human-computer interaction takes place. Web interfaces are now integrated in overall service provision, and are designed for a huge and diversified set of potential users, in an uncontrolled context. With the aim of understanding customer interaction needs and improving the methods of requirements elicitation in the web context, a qualitative study of a multi-channel Portuguese bank was made. The results obtained so far indicate that Interaction Design and Services Marketing have strong complementarities. The Marketing perspective is especially useful with regard to the study of customer experience requirements, which are increasingly influential in customer decisions to adopt Internet services. Essential use cases are also very useful in the multiple platform service context, as they allow the elicitation of experience requirements in a technology-independent way, and therefore allow an integrated management of the different interaction channels.

Abstract
A large variety of techniques have been developed to solve or approximate the solution of multiattribute ranking problems. From such techniques, several implicit or explicit partial orders, defined on the same set of alternatives, are obtained (in many cases, by pairwise comparisons) with the goal of determining a linear order. Often, this goal is attained by assigning positive weights to each partial order relation. However, the imprecise judgments of the pairwise comparisons as well as other factors lead to inconsistencies which have been analyzed in an extensive literature devoted to this type of problem. In this paper, numerical results about linear extensions of weighted sum relations are applied to the recognition of pairwise imprecise judgments between alternatives as well as to the confirmation of a ranking solution as a linear extension of a quasi-order defined by a weighted sum of binary preference relations. (C) 2003 Wiley Periodicals, Inc.

Abstract
This paper presents some concepts related with the development of a "model generator" for simulating supply chain systems. Such concepts arise not only from the object point of view taken over this system, but also from our intention to synthesise the behaviour of such kind of systems in a more general form, in particular concerning the events and activities related with suppliers, factories, warehouses, retailers, and even the last customers, which in fact trigger the flow of materials and information on the chain. Unlike the static approaches usually used for strategic purposes, where parameters like the time of delivery or the average rate of material flow are held as inputs to the system, the ideas described here consider a dynamic representation of the supply chain in which those parameters are results of some detailed simulation process. what gives this approach the ability of modelling those systems starting from the less abstract point of view to a more abstract representation. The result is a more realistic picture of the dynamics involved. Due to this fact, this approach could be seen as being more directed to managers than to strategists. Nevertheless, the objective is also that the models can be used to simulate either short or long periods of time, revealing their usefulness also for strategic analysis. The basis of these ideas is to consider the flow of products, information and money between any elements in the chain as a general form of customer-supplier exchange activity, and also by treating each of those elements as inheriting from a single element which includes the basic behaviour (and resources) of a factory, warehouse and retailer. A description of such element will be made. explaining its structure and the associated fixed and variable costs of its various processes. As we will see, many parameters considered inputs to other modelling techniques will appear here as outputs. giving the analyst more interesting data with which it can measure the supply chain performance by means of any statistical methods.

Abstract
This paper describes a new heuristic for the nesting problem based on a 2-exchange neighbourhood generation strategy. This mechanism guides the search through the solution space consisting of the sequences of pieces and relies on a low-level placement heuristic to actually convert one sequence in a feasible layout. The placement heuristic is based on a bottom-left greedy procedure with the ability to fill holes in the middle of the layout at a later stage. Several variants of the 2-exchange nesting heuristic were implemented and tested with different initial solution ranking criteria, different strategies for selecting the next solution, and different neighbourhood sizes. The computational experiments were based on data sets published in the literature. In most of the cases, the 2-exchange nesting algorithm generated better solutions than the best known solutions.