1. Proceedings
  2. I3M
  3. 2018
  4. MAS
  5. 10.46354/i3m.2018.mas.023

Simulation-based planning and optimization of an automated laundry warehouse using a Genetic Algorithm

  • a Marcel Müller , 
  • b Tobias Reggelin ,
  • c Stephan Schmidt 
  • a,b,c Otto von Guericke University Magdeburg, Germany
Cite as
Müller M., Reggelin T., Schmidt S. (2018). Simulation-based planning and optimization of an automated laundry warehouse using a Genetic Algorithm. Proceedings of the 17th International Conference on Modeling & Applied Simulation (MAS 2018), pp. 153-158. DOI: https://doi.org/10.46354/i3m.2018.mas.023

Abstract

The planning of logistics systems is a complex task with important decisions to make. Simulation models can help already in the early planning process of these systems. Usually they only provide a visualization of the different planned concepts but with modern genetic algorithm it is possible to provide even more support. Numerous parameters are not yet fixed at this point of a planning process. A dynamic model with flexible parameters and a genetic algorithm (GA) can already deliver good approximated solutions. An exemplary procedure for using this GA in the context of the research and development project ""LOCSys"" (Laundry Order Consolidation System) is presented in this paper. We use the genetic algorithm to find good approximated parameters for an optimised throughtput by changing the dimensions and control parameters of a warehouse with an automated picking and retrieval unit.

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