| dc.description.abstract | The Covid 19 pandemic has had a severe influence on the entire world, especially the
economy and industry. Numerous businesses work to enhance their systems in an effort
to cut costs and boost productivity, particularly in the logistics and supply chain sectors.
One of the most crucial components of the supply chain, the warehouse, is constantly
in need of improvement. The products are divided into several batches for the picking
process in the warehouse to reduce overall tardiness. The order batching model is
proposed in this research utilizing two distinct methods: a mathematical model using
Cplex and a grouped genetic algorithm model using Python. The second model was
designed to handle larger cases, since the previous model could only be solved with
tiny instances in a fair amount of time. Next, the routing technique is suggested
following batching and contrasted with common routing approach to assess
performance. | en_US |
