Genetic algorithms for layout optimization in crossdocking operations of a manufacturing plant

Abstract

In this study, we use genetic algorithms to optimize the lane layout associated with the crossdocking operation at the Toyota Motor Manufacturing plant in Georgetown, Kentucky, USA. A genetic algorithm solution can be obtained within seconds, whereas an exhaustive search would require a computing time of over five days on a 1 GHz Intel Pentium III. The results of this study show that a simple rearrangement of the lanes will lead to a decrease in workload of nearly 34% in the crossdocking area and ultimately result in an overall reduced lead time.

Keywords:

• Distribution/logistics
• Facility layout
• Crossdocking
• Artificial intelligence
• Genetic algorithms