A Bi-Objective Approach for Determining Optimal Order Picking Planning Strategy with Ergonomic Load Evaluation
Authors: Rifat Gurcan Ozdemir
Abstract: The main concern in many warehouse management systems is to arrange picking strategies for only time and cost considerations. However, the central operation in warehouse systems is order picking which involves highly physical load due to lifting and handling works. Therefore, load balance should be an integral part of order-picking planning strategies for a successful warehouse management system. This study focuses on determining order picking strategy by assigning orders to the pickers to minimize load imbalance and the total cost of order-picking operations. Ergonomic risk values of picking orders from the shelves are obtained by digital human modeling (DHM) via JACK software. The values for the ergonomic risk of the orders are then used to determine the load of each picker based on the assigned orders. The study is conducted in a warehouse working as a retailer of furniture and home decoration items. The main point of the study is to observe the ergonomic risks in terms of lower back compression force (LBCF) and integrate the results of ergonomic risks into a bi-objective mathematical model to determine an optimal order-picking strategy. The developed bi-objective model solves the order assignment with minimum picking cost and minimum imbalance ergonomic load among pickers. The study evaluates different order assignment strategies such as first come first serve (FCFS), highest ergonomic load order (HELO), lowest ergonomic load order (LELO), longest picking time order (LPTO), and shortest picking time order (SPTO). The results are used to construct a non-dominated set of solution alternatives in order to observe the impact of the order assignment strategy on the objective functions. The developed quantitative approach is used to evaluate the current strategy (FCFS) and compare it with the alternative strategies (HELO, LELO, LPTO, and SPTO). Finally, the suggestions for implementing the real-life numerical case are presented.
Keywords: Ergonomic risk assessment, Order picking, Digital Human Modeling, Mathematical Modelling
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