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Landscape analysis in adaptive metaheuristics for grid computing. (English) Zbl 1200.68281

Xhafa, Fatos (ed.), Parallel programming, models and applications in grid and P2P systems. Amsterdam: IOS Press (ISBN 978-1-60750-004-9/hbk; 978-3-540-68844-0/ebook). Advances in Parallel Computing 17, 313-344 (2009).
Summary: An ensemble of local search algorithms are discussed and analyzed, having different initial landscape perspectives as starting point – the conformational sampling problem is considered as a case study. Grid enabled hierarchical and multistage distributed evolutionary algorithms have been addressed in previous studies, combining complementary techniques and relying on different coordination models. For algorithmic constructions following the aforementioned outlines, the per se exploration results in an emergent behavior of the system. Nevertheless, in order to encompass a large spectrum of exploration characteristics and to harness the complete power of the combined techniques, landscape analysis has to be employed for guiding the exploration process. Due to the high complexity of real-life applications, landscape analysis represents a foreword measure in this direction, providing the means for adapting the exploration process as determined by the search landscape structure.
For the entire collection see [Zbl 1175.68024].

MSC:

68W15 Distributed algorithms
68P10 Searching and sorting
68T20 Problem solving in the context of artificial intelligence (heuristics, search strategies, etc.)
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