Metaheuristics for a new MINLP model with reduced response time for on-line order batching

With increase in the inventory of stored items and in the number of orders received, the picking process and the response time gain greater importance. It should be noted that, in order to enhance the efficiency of warehouse management system, effective correlation and coordination between order batching and order picking process is of crucial role. In this paper, novel mixed integer nonlinear programming for on-line order batching is proposed for improving performance of the warehouse which in turn results in reducing the response time and idle times. The proposed method is based on a blocked warehouse using a zoning system, which is called Online Order Batching in Blocked Warehouse with One Picker for each Block (OOBBWOPB). The mentioned model is solved by using two algorithm of artificial bee colony (ABC) and Ant-colony (ACO). For proving the analyses and claims, two numerical examples as cases 1 and 2 are defined and analyzed by this algorithms in MATLAB environment. Based on the results, the proposed warehouse shows better performance with a substantial reduction in the average response time of a set of customer orders compare to zhang et al. (2017) results. It’s noteworthy that the ACO yields better results than ABC.