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

Volume

3

fYear

2009

Firstpage

242

Lastpage

244

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;

fLanguage

English

Publisher

ieee

Conference_Titel

Intelligent Computation Technology and Automation, 2009. ICICTA '09. Second International Conference on

Print_ISBN

978-0-7695-3804-4

Type

conf

DOI

10.1109/ICICTA.2009.525

Filename

5287948