|dc.description.abstract||Due to the popularity of internet ordering and intelligent logistic and supply chain management systems, customers tend to order more frequently, in smaller quantities, and they require more customized service. As a result, the turn-over rate of SKUs in many warehouses is significantly increasing. The distribution center in this study is zone-based carton picking system and it is dynamically replenished with specific SKUs for next pick wave after pickers complete the picking for the current pick wave. In other words, the picking area is completely reslotted between each pick wave. In this distribution center environment, the long-term demand is of limited value in determining the appropriate assignment of SKUs to slots and items to cartons for the specific pick wave. Thus, the distribution center has two NP-hard assignment problems: slotting –assigning SKUs to slots in the picking area; and cartonization – assigning individual items to cartons. The two primary assignment problems are interrelated and are simultaneously solved at the beginning of the pick wave.
The primary objective in this dissertation is to develop an efficient iterative heuristic methodology for systematically solving two interrelating complex decision problems based on simulated annealing slotting heuristic using correlated SKUs and cartonization heuristic using bin-packing heuristic considering slotting. The proposed heuristic improves the performance of makespan of pickers assigned in each zone compared to two independent heuristics being given does not guarantee a good solution.||en