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Bio-Mimetic Approaches in Management Science

Produktform: E-Buch Text Elektronisches Buch in proprietärem

Management Science is often confronted with optimization problems characterised by weak underlying theoretical models and complex constraints. Among them, one finds data analysis, pattern recognition (classification, multidimensional analysis, discriminant analysis) as well as modelling (forecasting, confirmatory analysis, expert system design). In recent years, biomimetic approaches have received growing attention from Marketing, Finance and Human Resource researchers and executives as effective tools for practically handling such problems. Biomimetic approaches include a variety of heuristic methods - such as neural networks, genetic algorithms, immunitary nets, cellular automata - that simulate nature's way of solving complex problems and, thus, can be considered as numerical transpositions of true life problem solving. presents a selection of recent papers on biomimetic approaches and their application to Management Science. Most of these papers were presented at the last ACSEG/CAEMS International Congresses (Approches Connexionnistes en Sciences Economiques et de Gestion/Connectionnist Approaches in Economics and Management Science). All papers combine the discussion of conceptual issues with illustrative empirical applications, and contain detailed information on the way heuristics are practically implemented. The advantages and limits of the biomimetic approaches are discussed in several of the papers, either by comparing these approaches with more classical methods (logit models, clustering), or by investigating specific issues like overfitting and robustness. Synthesizing overviews are provided, as well as new tools for coping with some of the limitations of biomimetic methods. weiterlesen

Dieser Artikel gehört zu den folgenden Serien

Elektronisches Format: PDF

Sprache(n): Englisch

ISBN: 978-1-4757-2821-7 / 978-1475728217 / 9781475728217

Verlag: Springer US

Erscheinungsdatum: 09.03.2013

Seiten: 208

Herausgegeben von Jacques-Marie Aurifeille, Christopher Deissenberg

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