Slotting Optimization Model and Algorithm for Concerning the Correlation in Hybrid Travel Policy

Abstract

In the periodic picking background, we researched the influence of the picking correlations between Stock Keeping Units (SKUs), established dynamic location assignment model to minimize the total picking time, developed a particle swarm optimization (PSO) based on the correlated SKUs. We set the cube-per-order-index (COI) solution as initial solution, used correlation strength to update the velocity and position of particles and assigned correlated SKUs to adjacent slots according to the optimal location sequence. The result shows that in zone-based wave-picking system with hybrid touring policy, the solution quality of PSO is always better than COI, the improvement of PSO is 2.50%~13.9% and average improvement is 2.84%~12.53%; the correlation has significant impact on the picking efficiency.