Development of an online order batching algorithm in blocked warehouse

The route length is taken by the operator is deemed to be an effective parameter in minimization of response time's orders in a typical warehouses with a manual picking system, in which the picker collects goods through depot. Therefore, reduction of the route length has been increasingly received considerable attention from the scholars in this area. The response time and system's costs are regarded as the most essential components necessitating the utilization of order batching process for rival companies, particularly when there is no information about time and amount of inbound orders, and even when there is substantial amounts of orders in large warehouses working with an online order entry system. This process has a profound impact on reducing the route length and thus decreasing the organization costs. Present study takes aim at investigation of order classification in the first time in the picker-to-part system as a manual picking system and an online order batching system, with the intent of minimizing the turnover time and idle time. Besides, an order batching model in a blocked warehouse using a zoning system is proposed which is called Online Order B arching in Blocked Warehouse with One Picker for each Block (OOBBWOPB). This is investigated by online order entry system using a nonlinear programming model based on meta-heuristic method of Teaching Learning Based Optimization (TLBO) algorithm. The average turnover time of the customer's orders is witnessed insignificant reduction using the proposed model, which lead to greatly enhance the total efficiency of warehouse system.