@inproceedings{469,
  abstract     = {{Production  scheduling  has attracted  the  interest  of  production  economics  communities  for  decades,  
but there is still  a  gap between academic research, real -world problems, operations research and  simulation.  Genetic  Algorithms  (GA) represent a technique that has already been applied to a variety of combinatorial problems. 
Simulation can be used to find a solution to problems through repetitive simulation runs or to prove a solution 
computed by an optimization algorithm. We will explain the  application of two special GAs for job -shop and resource-
constrained  project scheduling  problems trying  to bridge the gap between problem  solving  by  algorithm  
and by simulation. Possible goals for scheduling  problems are to minimize the makespan of a production program or to increase the due -date reliability of jobs or possibly any goal which can be described in a mathematical expression. The approach focuses on integrating a GA into a commercial software product and verifying the results with simulation.}},
  author       = {{Zülch, Gert and Steininger, Peter and Gamber, Thilo Gerhard and Leupold, Miachael}},
  booktitle    = {{Proceedings of the 2009 Winter Simulation Conference; Energy Alternatives}},
  editor       = {{Rossetti, M.D. and Hill, R.R. and Johansson, B. and Dunkin, A. and Ingalls, R.G.}},
  isbn         = {{9781424457700}},
  location     = {{New York}},
  pages        = {{2238--2249}},
  title        = {{{Generating, Benchmarking and Simulating Production Schedules – From Formalisation to Real Problems}}},
  year         = {{2009}},
}