Abstract
This article introduces several mathematical formulations for the joint order picking problem (JOPP) in low-level picker-to-part warehousing systems. In order to represent real warehousing environments, the proposed models minimize performance measures such as travel distance, travel time and tardiness, considering multi-block warehouses, due dates, and multiple pickers. The number of constraints and decision variables required for each proposed model is calculated, demonstrating the complexity of solving medium and long-sized problems in reasonable computing time using exact methods. The proposed models can be followed as a reference for new solution methods that yield efficient and fast solutions.
Highlights
Within warehouse operations, the order picking is responsible for retrieving products from shelves to fulfill customer orders, while pickers use a picking device through the warehouse
RESEARCH METHOD The following joint order picking problem (JOPP) formulations are based on mathematical programming models, proposing an objective function to optimize and constraints using decision variables to integrate the order picking problems addressed in the joint order batching and picker routing problem (JOBRP), JOBARP, and JOBASRP
The size of the problems related to the proposed formulations for the JOBRP, JOBARP and JOBASRP has been calculated through the number of constraints and binary variables according to storage locations and customer orders
Summary
The order picking is responsible for retrieving products from shelves to fulfill customer orders, while pickers use a picking device through the warehouse. Poor picking performance results in non-fulfillment of deliveries to customers, incorrect shipments, high labor costs, and additional shipping costs [1]. This is even more evident in picker-to-part systems, where the order picking becomes a repetitive and labor-intensive process [2] generating between 50-70% of the operating costs of a warehouse [3]. In order to optimize order picking operations, several problems like the order batching problem (OBP), batch sequencing problem (BSP), batch assignment problem (BAP), and picker routing problem (PRP) must be solved. The PRP plans tours to be followed by the pickers to retrieve all the items from the assigned batches in the shortest time and distance [6]
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callMore From: Bulletin of Electrical Engineering and Informatics
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
