Abstract
In this paper we present Khronos, a framework for Discrete Event Simulation (DES) in Python. Its essential objective is to provide a powerful, general, and easy-to-use tool for simulation programmers/users. In the form of a programming library, Khronos accomplishes a seamless combination of DES with Python, taking advantage of many of the language's features in addition to maintaining its generality, power, and simplicity. The final product is a framework which releases the user from the low-level details of DES (e.g., managing the event schedule, simulation clock, or real-time synchronization), also providing base classes for entities/resources, and a flexible set of primitives for describing the dynamic behaviors of these elements. Most importantly, the resulting simulation programs are intuitive to write, and inherently very readable. We highlight the main features of the Khronos library in a tutorial manner, presenting a simple illustrative example.

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This paper presents a case study of a web application for inventory management of electronics laboratories. The iLab project efficiently manages the inventory, requests, users (borrowings, purchases, etc.) and associated historic and workflow information. This enables users to queue requests and track their status. This project differs from the existing applications from this kind, since it not only serves administrative proposes, but also the users requirements. It was also developed with tools that ensure ease of development and deployment, while maintaining high performance, stability, security and future growth. In order to ensure a low "Total Cost of Ownership" application, freeware and web based tools were used. Future work includes Business to Business communications with large suppliers and optimization of the information stored in the database.

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This paper presents an innovative software called FEUP Fuzzy Tool. It was developed by teacher and students as an attempt to provide means to easily control non-linear plants and Multiple Input Multiple Output systems under soft real time constraints with the advantages offered by Fuzzy Logic controllers such as the usage of linguistic variables. The tool was partially developed in the classes and is currently used for investigation and educational purposes. This document discusses the features recently added to the toolbox, highlighting some very interesting capacities such as the capacity to export the developed fuzzy controllers to embedded systems. It is also given some insight of what it is currently been developed.

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In this paper, we present greedy randomised dispatching heuristics for the single-machine scheduling problem with quadratic earliness and tardiness costs and no machine idle time. The several heuristic versions differ, on the one hand, on the strategies involved in the construction of the greedy randomised schedules. On the other hand, these versions also differ on whether they employ only a final improvement step or perform a local search after each greedy randomised construction. The proposed heuristics were compared with existing procedures as well as with optimum solutions for some instance sizes. The computational results show that the proposed procedures clearly outperform their underlying dispatching heuristic, and the best of these procedures provide results that are quite close to the optimum. The best of the proposed algorithms is the new recommended heuristic for large instances as well as a suitable alternative to the best existing procedure for the larger of the middle-sized instances.

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