Abstract
This paper presents a genetic algorithm for the resource constrained multi-project scheduling problem. The chromosome representation of the problem is based on random keys. The schedules are constructed using a heuristic that builds parameterized active schedules based on priorities, delay times, and release dates defined by the genetic algorithm. The approach is tested on a set of randomly generated problems. The computational results validate the effectiveness of the proposed algorithm. (C) 2007 Published by Elsevier B.V.

Abstract
In this paper it is proposed an efficient contingency screening and ranking algorithm for assessment and classification of multiple contingencies of an Electric Power System using the Rough Set theory. The developed methodology produces a classification of the system operation in five possible states: normal, alert, emergency, in-extremis and restorative. These different operating states correspond to six levels of security: secure, alert, correctively secure, alert no correctable, emergency and restorative. The states can be classified horizontally as secure, that correspond to the normal state and insecure for the remaining ones. The developed computer programs, the SECURsySTEM were applied to the IEEE 118 busbars test power network and results are presented and analyzed.

Abstract
This paper presents the Gene Fragment Competition concept that can be used with Hybrid Genetic Algorithms specially in signal and image processing. Memetic Algorithms have shown great success in real-life problems by adding local search operators to improve the quality of the already achieved "good" solutions during the evolutionary process. Nevertheless these traditional local search operators don't perform well in highly demanding evaluation processes. This stresses the need for a new semi-local non-exhaustive method. Our proposed approach sits as a tradeoff between classical Genetic Algorithms and traditional Memetic Algorithms, performing a quasi-global/quasi-local search by means of gene fragment evaluation and selection. The applicability of this hybrid Genetic Algorithm to the signal processing problem of Polyphonic Music Transcription is shown. The results obtained show the feasibility of the approach.

Abstract
Developed countries have made significant efforts to integrate Unmanned Aerial Vehicle (UAV) operations in controlled aerial space due to a rising interest of using UAVs for civilian as well as military purposes. This paper focuses on looking for reliable solutions and a way to validate an autonomous multiagent control system through a different variety of Flight Simulations. This study has two main lines, the first being the use of multiagent systems in UAVs, aiming at a fully autonomous control. The second and focal line is a survey about the variety of simulation systems dedicated to aerodynamics and aircrafts, comparing them and their feasibility to validate the developed multiagent control system. One critical factor is hazard situations, like emergency landing without runway or equipment failure, which should be predicted in an automated system. Most flight simulators are not realistic enough to validate a multiagent algorithm in hazard situations. At the same time, it is impossible to predict every type of failure in real world. The boundaries of simulation should be very well enclosured in order to present results using simulation.

Abstract
The electrical compensation of chromatic dispersion (CD) and polarization mode dispersion (PMD) in a coherent optical system exploiting polarization multiplexing is discussed in this paper. The benefits of combining a phase estimation algorithm with a decision directed least-mean-square equalizer in a feedback configuration is reported.

Abstract