TY - JOUR
T1 - A Special Case of the Multiple Traveling Salesmen Problem in End-of-aisle Picking Systems
AU - Baardman, Lennart
AU - Roodbergen, Kees Jan
AU - J. Carlo, Héctor
AU - Schrotenboer, Albert
PY - 2021/9/1
Y1 - 2021/9/1
N2 - This study focuses on the problem of sequencing requests for an end-of-aisle automated storage and retrieval system in which each retrieved load must be returned to its earlier storage location after a worker has picked some products from the load. At the picking station, a buffer is maintained to absorb any fluctuations in speed between the worker and the storage/retrieval machine. We show that, under conditions, the problem of optimally sequencing the requests in this system with a buffer size of m loads forms a special case of the multiple traveling salesmen problem in which each salesman visits the same number of cities. Several interesting structural properties for the problem are mathematically shown. In addition, a branch-and-cut method and heuristics are proposed. Experimental results show that the proposed simulated annealing-based heuristic performs well in all circumstances and significantly outperforms benchmark heuristics. For instances with negligible picking times for the worker, we show that this heuristic provides solutions that are, on average, within 1.8% from the optimal value.
AB - This study focuses on the problem of sequencing requests for an end-of-aisle automated storage and retrieval system in which each retrieved load must be returned to its earlier storage location after a worker has picked some products from the load. At the picking station, a buffer is maintained to absorb any fluctuations in speed between the worker and the storage/retrieval machine. We show that, under conditions, the problem of optimally sequencing the requests in this system with a buffer size of m loads forms a special case of the multiple traveling salesmen problem in which each salesman visits the same number of cities. Several interesting structural properties for the problem are mathematically shown. In addition, a branch-and-cut method and heuristics are proposed. Experimental results show that the proposed simulated annealing-based heuristic performs well in all circumstances and significantly outperforms benchmark heuristics. For instances with negligible picking times for the worker, we show that this heuristic provides solutions that are, on average, within 1.8% from the optimal value.
KW - Automated storage/retrieval systems
KW - Multiple traveling salesmen problem
KW - Scheduling
KW - Warehousing
UR - http://www.scopus.com/inward/record.url?scp=85117249622&partnerID=8YFLogxK
U2 - 10.1287/trsc.2021.1075
DO - 10.1287/trsc.2021.1075
M3 - Article
SN - 0041-1655
VL - 55
SP - 1151
EP - 1169
JO - Transportation Science
JF - Transportation Science
IS - 5
ER -