Bøger af Roberto Battiti

Thisbookcontainstherefereedproceedingsofthe1stIFIP-TC6WorkingCon- rence on Wireless-On-Demand Network Systems, WONS 2004. It was sponsored by the IFIP Working Groups 6.3 (Performance of Computer and Commu- cation Networks)and6.8(Mobile and Wireless Communications), and aimed at becoming a premier international forum for discussions between researchers and practitioners interested in the evolution of Wireless Internet Access toward on-demand networking. Ad hoc, routing, localization, resource management, - curity, applications, performance and analytical models were topics covered in depth by technical papers in this book. Theconferencereceived77submissionsfrom22countries,showingthewor- wide interest. With so many papers to choose from, the Technical Program Committee's job, providing a conference program with the highest quality, was challenging and time consuming. We ?nally selected 25 full papers for presen- tion in the conference technical sessions. To give researchers the opportunity to present the novel ideas they are starting to explore, we included in the technical program a poster session devoted to presenting preliminary research results: 7 short papers were selected for presentation in this session. Accepted papers and posters came from 15 di?erent countries. The technical program also included a keynote speech "e;Ad Hoc Wireless Networks: Protocols and Applications"e; by Prof. Mario Gerla, and a panel s- sion devoted to the discussion of the conference topics between academics and industry representatives. This event would not have been possible without the enthusiasm and hard work of a number of colleagues. A special thanks to the TPC members, and all the referees, for their invaluable help in reviewing the papers for WONS 2004.

This volume collects the accepted papers presented at the Learning and Intelligent OptimizatioN conference (LION 2007 II) held December 8-12, 2007, in Trento, Italy. The motivation for the meeting is related to the current explosion in the number and variety of heuristic algorithms for hard optimization problems, which raises - merous interesting and challenging issues. Practitioners are confronted with the b- den of selecting the most appropriate method, in many cases through an expensive algorithm configuration and parameter-tuning process, and subject to a steep learning curve. Scientists seek theoretical insights and demand a sound experimental meth- ology for evaluating algorithms and assessing strengths and weaknesses. A necessary prerequisite for this effort is a clear separation between the algorithm and the expe- menter, who, in too many cases, is "e;in the loop"e; as a crucial intelligent learning c- ponent. Both issues are related to designing and engineering ways of "e;learning"e; about the performance of different techniques, and ways of using memory about algorithm behavior in the past to improve performance in the future. Intelligent learning schemes for mining the knowledge obtained from different runs or during a single run can - prove the algorithm development and design process and simplify the applications of high-performance optimization methods. Combinations of algorithms can further improve the robustness and performance of the individual components provided that sufficient knowledge of the relationship between problem instance characteristics and algorithm performance is obtained.

This book presents the main principles of reactive search and intelligent optimization and clearly shows how they can be used in problem solving. The book will be of interest to anyone working in the meta-heuristics.