Title :
Optimizing Dynamic Logistics Allocation on Improved Ant Colony Algorithm
Author :
Na, Li ; Shoubin, Wang
Author_Institution :
Dept. Manage. Eng., Tianjin Inst. of Urban Constr., Tianjin, China
Abstract :
Facing distribution channel restructuring and quick response to the diversity of customer order demands, the specialized logistics companies have been urgently requested with the capability of allocating limited resources in the process of logistics allocation control and decision. Ant colony algorithm is proposed aiming at solving the logistics allocation problem, and pheromone updating strategy is ameliorated to improve the efficiency. The result of experiments demonstrates that the optimal or nearly optimal solutions to the logistic distribution routing can be quickly obtained by improved ant colony algorithm.
Keywords :
logistics; optimisation; resource allocation; ant colony algorithm; customer order demand; distribution channel restructuring; dynamic logistics allocation; logistics allocation control; logistics allocation decision; logistics companies; pheromone updating strategy; Ant colony optimization; Chaos; Chaotic communication; Cities and towns; Logistics; Resource management; Routing; Scheduling algorithm; Vehicle dynamics; Vehicles;
Conference_Titel :
Intelligent Computation Technology and Automation, 2009. ICICTA '09. Second International Conference on
Print_ISBN :
978-0-7695-3804-4
DOI :
10.1109/ICICTA.2009.525
