Learning in automated manufacturing : a local search approach; Production and logistics. Dieser Artikel ist nicht verfügbar.Learning in automated manufacturing : a local search approach; Production and logistics

The central purpose of this book is to acquaint the reader especially with the cases of local search based learning as well as to introduce methods of constraint based reasoning, both with respect to their use in automated manufacturing. We restrict our attention to job shop scheduling as well as to one-machine scheduling with sequence dependent setup times. Additionally some design and planning issues in flexible manufacturing systems are considered. General purpose search methods which in particular include methods from local search such as simulated annealing, tabu search, and genetic algorithms, are the basic ingredients of the proposed intelligent knowledge-based scheduling systems, enriched by a number of constraint-based local decision rules in order to introduce problem specific knowledge.

Prof. Dr. Florian Jaehn ist Wirtschaftsmathematiker und Betriebswirt und nach einer Professur an der Universität Augsburg seit 2017 Inhaber eines Lehrstuhls für Management Science und Operations Research an der Helmut-Schmidt-Universität in Hamburg. Prof. Dr. Erwin Pesch ist Mathematiker und Betriebswirt und nach einer Professur an der Universität Bonn seit 2001 Inhaber eines Lehrstuhls für Wirtschaftsinformatik an der Universität Siegen. Seit 2016 ist er zudem Direktor des Centers für Advanced Studies in Management an der HHL Leipzig.