Production scheduling dictates highly constrained mathematical models
with complex and often contradicting objectives. Evolutionary algorithms
can be formulated almost independently of the detailed shaping of the
problems under consideration. As one would expect, a weak formulation of
the problem in the algorithm comes along with a quite inefficient
search. This book discusses the suitability of genetic algorithms for
production scheduling and presents an approach which produces results
comparable with those of more tailored optimization techniques.