Title of article :
Ant colony optimization algorithm to solve for the transportation problem
of cross-docking network
Author/Authors :
Rami Musa a، نويسنده , , *، نويسنده , , Jean-Paul Arnaout b، نويسنده , , Hosang Jung، نويسنده ,
Issue Information :
ماهنامه با شماره پیاپی سال 2010
Abstract :
This paper addresses the transportation problem of cross-docking network where the loads are transferred
from origins (suppliers) to destinations (retailers) through cross-docking facilities, without storing
them in a distribution center (DC). We work on minimizing the transportation cost in a network by loading
trucks in the supplier locations and then route them either directly to the customers or indirectly to
cross-docking facilities so the loads can be consolidated. For generating a truck operating plan in this type
of distribution network, the problem was formulated using an integer programming (IP) model and
solved using a novel ant colony optimization (ACO) algorithm. We solved several numerical examples
for verification and demonstrative purposes and found that our proposed approach finds solutions that
significantly reduce the shipping cost in the network of cross-docks and considerably outperform
Branch-and-Bound algorithm especially for large problems.
Keywords :
Cross-docking , Transportation planning , Ant colony optimization (ACO) , Metaheuristics , Integer programming
Journal title :
Computers & Industrial Engineering
Journal title :
Computers & Industrial Engineering