General Variable Neighborhood Search for the Order Batching and Sequencing Problem

Abstract

Warehousing has been found as an essential issue by the industry in the last few years, being a key part of the supply chain management. It mainly focuses its attention on moving and storing materials in warehouses by performing different activities such as shipping, receiving, and picking operations. The profits obtained by warehouse management systems strongly depends on how customer orders, containing a set of goods, are collected. This picking process consists in collecting goods (items) before shipment to satisfy the orders of the customers. The Order Batching and Sequencing Problem (OBSP) involves the process of collecting orders in a warehouse by grouping orders into batches with a maximum fixed capacity. In the context of the OBSP, each order has a certain due date, i.e., it must be collected before a specific time. Otherwise, it has associated a tardiness penalty. The problem then consists in grouping orders into batches, sequencing the batches and finding a route to collect each batch, in such a way that the total tardiness is minimized. In this paper we propose a heuristic approach based on the Variable Neighborhood Search methodology to address the problem. Additionally, we provide an extensive experimental comparison between our procedure and the best previous method found in the related literature. The experimentation reveals that our algorithm improves the state of the art in both, quality and computing time. This fact is finally confirmed by non-parametric statistical tests.

Publication
European Journal of Operational Research
Eduardo García Pardo
Eduardo García Pardo
Associate Professor

Miembro fundador del grupo de investigación GRAFO, cuya línea de investigación principal es el desarrollo de algoritmos para abordar problemas de optimización, temática sobre la que versa la Tesis Doctoral del investigador y en la que se enmarcan sus publicaciones más destacadas.

Abraham Duarte
Abraham Duarte
Full Professor

Abraham Duarte is Full Professor in the Computer Science Department at the Rey Juan Carlos University (Madrid, Spain). He has done extensive research in the interface between computer science, artificial intelligence, and operations research to develop solution methods based on Computational Intelligence (metaheuristics) for practical problems in operations-management areas such as logistics and supply chains, telecommunications, decision-making under uncertainty and optimization of simulated systems.