Skill-Based Joint Order Batching and Picker Routing Problem

Abstract

The problem of batching orders and routing orders in picker-to-parts warehouses is intensively studied in the research literature, but the impact of individual differences among pickers or forklift operators and their skills are rarely taken into consideration. Therefore, we propose a model that simultaneously does order batching and routing while taking advantage of the skills of each worker. This approach optimizes the total batch execution time, and reduces the physical and mental effort of workers, since they are likely to perform easy tasks according to their capabilities. Based on empirical data on workers’ skills and tasks characteristics, we present an integer linear programming model based on the classic joint order batching and picker routing problem, with the novelty that individual workers’ skills are taken into account while assigning tasks to workers. Using real-world instances, the computational experiments show that it is possible to solve instances with up to 20 orders to proven optimality within a time limit of 1 hour, without considerably increasing the total distance traveled compared to the classic approach which only focuses on minimizing this criterion.