Order allocation and sorting optimization for AMR-based parts-to-picker system
LIU Zhishuo
ZHANG Sirui
HAO Mengjun
Abstract：This study addresses the integrated optimization problem of order allocation,processing se-quence,and shelf access sequence in a multi-picking-station scenario of an Autonomous Mobile Robot(AMR)-based parts-to-picker picking system.The Order Allocation and Sequencing Problem(OASP)in a multi-picking-station scenario is proposed,which jointly optimizes how orders are assigned to picking stations,the processing sequence of orders at each station,and the shelf access sequence.A mixed-integer programming model is formulated with the objective of minimizing total order picking time.A Variable Neighborhood Search Algorithm(VNSA)is developed,which batches orders based on order similarity to generate a greedy initial solution.The algorithm incorporates four types of local search neighborhoods,including shelf replacement and order reallocation jitter operators,order exchange/insertion,and shelf sequence adjustments,combined with a dynamic switching mechanism to iteratively improve the solution.The performance of VNSA is compared with that of the CPLEX solver.Results demonstrate that VNSA outperforms CPLEX in solution speed and accuracy on small-scale instances,and shows significant improvements in initial solution quality on large-scale instances,verifying the effectiveness of joint optimization of order allocation and sequencing.Moreover,order picking time exhibits a negative correlation with the number and capacity of picking stations,and a positive correlation with the load balancing coefficient.
Keywords：autonomous mobile robotparts-to-picker order picking systemorder allocationorder sequencingshelf sequencingvariable neighborhood search algorithm
Publication Date：2025-08-30
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：10( 132-141 )