Document Type

Research Paper

Publication Date

2012

Abstract

Many exiting slotting methods ignore the picking correlations between Stock Keeping Units (SKUs). In a previous paper, a mix integer program model for dynamic slotting to minimize the pick-wave makespan among all zones under some load balancing constraints was developed. In this paper, we develop an ant colony optimization with slot-exchange policy (ACO-SE) based on SKU correlation to assign the correlated SKUs to the adjacent slots in the same zone. The ACO-SE deposits pheromones between SKUs, uses local and global pheromone trail updates, and controls pheromone accumulation using the Max-Min rule. The main heuristic information is set to the correlation strength and the pick-times are introduced as the assisted heuristic information. A hybrid search mechanism was adopted to improve to global search efficiency. A slot exchange policy was proposed to re-slot the correlated SKUs based on the picks to ignore the proximity of SKUs and to make the farthest SKU for one carton closer to the initial point as far as possible. The promising computational results show that the ACO-SE has perfect convergence and very good CPU time. The solution quality of ACO-SE is always better than the Cube-per-Order-Index (COI), simulated annealing correlation (SA-C) heuristic; it has considerably faster convergence speed than SA-C. The result shows that in zone-based wave-picking system with return touring policy, the exact proximity of SKUs is not critical and that the correlated SKUs can be allocated to any locations along the path from the initial point to the other SKU’s location; the correlation strength has no obvious impact on the picking efficiency, but and correlation probability

Comments

Paper 36

Publication Title

Progress in Material Handling Research: 2012

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