A simulation-based immune genetic algorithm for the crane scheduling problem

نویسندگان

  • Huizhi Ren
  • Jian Tao
چکیده

The paper studied a multi-machine and multi-task warehouse crane scheduling problem. The collision between adjacent cranes needs to be avoided in the scheduling problem. Considering the involved operation requirement and condition, a process simulation model was formulated to evaluate a candidate crane schedule through rehearsing the crane operation process. Based on the process simulation, an immune genetic algorithm was developed to iteratively improve the crane schedule. The process simulation-based immune genetic algorithm was tested on a group of practical instances, which showed that it was effective for the crane scheduling problem.

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تاریخ انتشار 2015