Título:  A solution method for solving a case study of an order picking problem
Ponente:  Dra. Diana Lucia Huerta Muñoz
 

Resumen: Order picking is the process of collecting products from a specific location to complete customer orders. It is the most costly activity inside of a warehouse with up to 65% of the incurred costs (de Koster et al., 2007). On the other hand, two important and closely related problems to the order picking are the storage location of products and the order batching, which may affect the routes performed by pickers if those are not well-optimized. In the first one, the decision to take into account is where to place the items arriving at the warehouse considering that there are several and available locations (or racks) and, in the second one, the decision is to determine how to group customer orders in batches, which must be assigned later to pickers to perform the corresponding routes.

Although these three problems are commonly studied and solved independently, recent studies have shown that their integration may result in a greater improvement (Silva et al., 2020). The aim of this integration is to obtain the best storage location and batching decisions that minimize the total picking cost. We propose a mathematical model formulated as a Mixed-Integer Linear Programming (MILP) and preliminar approximate solution method composed of a construction heuristic and two local search procedures to solve a real-world case study of a Mexican company. Also, we provide some computational results to show their performance.