Planning and picking in small warehouses under industry-relevant constraints

Abstract

This work presents a procedure to plan the storage, picking sequences, and picking paths in warehouses, focusing on small businesses that may not afford the construction of designed-for-purposes storage facilities or use sophisticated picking strategies. The procedure considers storage spaces of irregular shapes and assumes the use of a picker-to-parts strategy. It considers constraints, such as proximity constraints and comprises three nested loops. The innermost loop uses the NetworkX package to find the shortest path between two locations. The intermediate loop uses the traveling salesperson problem implementation of Google OR-Tools to find the optimal path to collect the items in a given order. The third loop uses the simulated annealing method for optimal storage allocations. A class-based approach to simulated annealing optimization proposed in this work systematically improves the storage/picking configuration.