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Optimization Problems in Self-Organizing Networks
Modern computer networks or wireless ad-hoc networks offer a wide range of interesting optimization problems. Usual optimization goals are the minimization of the message delay in a Peer-to-Peer system or the minimization of the energy consumption of a wireless network. This thesis presents different kinds of algorithms to solve such optimization problems. Starting from the mathematical formulations for these problems, various global view optimization algorithms are presented. These algorithms are based on evolutionary algorithms and local search or similar heuristics. They can be used to quickly find near-optimal solutions, if a global view of the network is possible. As the participants in a computer network or a wireless ad-hoc network are autonomous nodes, distributed algorithms can be designed that enable these nodes to collectively solve the optimization problem. Four distributed algorithms are formulated and evaluated in this thesis, thus laying grounds for distributed optimization of networks. Using these algorithms, the network can be modelled as a self-optimizing network and the optimization problem can be approached without global view.
Major Companies of Europe 1990/91
Graham & Trotman, a member of the Kluwer Academic VOLUMES 1 &2 Publishers Group is one of Europe's leading publishers of MAJC?R COMPANIES OF EUROPE 1990/91, Volume 1, business information, and publishes company reference contaln~ us~ful information on over 4000 of the top annuals on other parts of the world as follows: comPB:nles In the European Economic Community, excluding the UK, nearly 1500 companies of which are MAJOR COMPANIES OF THE ARAB WORLD covered in Volume 2. Volume 3 covers nearly 1100 of the MAJOR COMPANIES OF THE FAR EAST & AUSTRALASIA top companies within Western Europe but outside the MAJOR COMPANIES OF THE U.S.A. European Economic Community. Altogether the three volumes of ...
Parallel Problem Solving from Nature - PPSN X
This book constitutes the refereed proceedings of the 10th International Conference on Parallel Problem Solving from Nature, PPSN 2008, held in Dortmund, Germany, in September 2008. The 114 revised full papers presented were carefully reviewed and selected from 206 submissions. The conference covers a wide range of topics, such as evolutionary computation, quantum computation, molecular computation, neural computation, artificial life, swarm intelligence, artificial ant systems, artificial immune systems, self-organizing systems, emergent behaviors, and applications to real-world problems. The paper are organized in topical sections on formal theory, new techniques, experimental analysis, multiobjective optimization, hybrid methods, and applications.
Parallel Problem Solving from Nature, PPSN XI
We are very pleased to present to you this LNCS volume, the proceedings of the 11th International Conference on Parallel Problem Solving from Nature (PPSN 2010). PPSN is one of the most respected and highly regarded c- ference series in evolutionary computation, and indeed in natural computation aswell.Thisbiennialeventwas?rstheldinDortmundin1990, andtheninBr- sels (1992), Jerusalem (1994), Berlin (1996), Amsterdam (1998), Paris (2000), Granada (2002), Birmingham (2004), Reykjavik (2006) and again in Dortmund in 2008. PPSN 2010 received 232 submissions. After an extensive peer review p- cess involving more than 180 reviewers, the program committee chairs went through all the review reports a...
LATIN 2004: Theoretical Informatics
This volume contains the proceedings of the Latin American Theoretical Inf- matics (LATIN) conference that was held in Buenos Aires, Argentina, April 5–8, 2004. The LATIN series of symposia was launched in 1992 to foster interactions between the Latin American community and computer scientists around the world. This was the sixth event in the series, following S ̃ ao Paulo, Brazil (1992), Valparaiso, Chile (1995), Campinas, Brazil (1998), Punta del Este, Uruguay (2000), and Cancun, Mexico (2002). The proceedings of these conferences were also published by Springer-Verlag in the Lecture Notes in Computer Science series: Volumes 583, 911, 1380, 1776, and 2286, respectively. Also, as before,...
Recent Advances in Memetic Algorithms
Memetic algorithms are evolutionary algorithms that apply a local search process to refine solutions to hard problems. Memetic algorithms are the subject of intense scientific research and have been successfully applied to a multitude of real-world problems ranging from the construction of optimal university exam timetables, to the prediction of protein structures and the optimal design of space-craft trajectories. This monograph presents a rich state-of-the-art gallery of works on memetic algorithms. Recent Advances in Memetic Algorithms is the first book that focuses on this technology as the central topical matter. This book gives a coherent, integrated view on both good practice examples and new trends including a concise and self-contained introduction to memetic algorithms. It is a necessary read for postgraduate students and researchers interested in recent advances in search and optimization technologies based on memetic algorithms, but can also be used as complement to undergraduate textbooks on artificial intelligence.
Pennsylvania Archives
A collection of documents supplementing the companion series known as "Colonial records," which contain the Minutes of the Provincial council, of the Council of safety, and of the Supreme executive council of Pennsylvania.
