Title :
Optimizing the route of logistics based on the hybrid ant colony algorithm
Author :
Chen, Weidong ; Tan, Yubo ; Wang, Feng ; Ding, Wei
Author_Institution :
Coll. of Inf. Sci. & Eng., Henan Univ. of Technol., Zhengzhou
Abstract :
The ant colony algorithm (ACA) has been successfully applied to several combinatorial optimization problems, but it has some shortcomings such as its slow computing speed, and it is easy to fall into local optimal. So a hybrid ant colony algorithm is proposed to optimize the ACA parameters. Firstly, the basic feasible solutions are solved by ACA, and then the quadratic optimal results are gotten by mutation operators of GA. At last the optimal solution is obtained for the vehicle routing problem. The algorithm is applied to the logistical delivery routing problem. The simulation results show that its optimization quality and efficiency is superior to the traditional ACA and the GA.
Keywords :
combinatorial mathematics; logistics; optimisation; transportation; combinatorial optimization problems; hybrid ant colony algorithm; logistics route; vehicle routing problem; Ant colony optimization; Educational institutions; Genetic algorithms; Genetic mutations; Heuristic algorithms; Information science; Logistics; Robustness; Routing; Vehicles; ant colony algorithm; genetic algorithm; logistics delivery routes; optimization; vehicle routing problem;
Conference_Titel :
Service Operations and Logistics, and Informatics, 2008. IEEE/SOLI 2008. IEEE International Conference on
Conference_Location :
Beijing
Print_ISBN :
978-1-4244-2012-4
Electronic_ISBN :
978-1-4244-2013-1
DOI :
10.1109/SOLI.2008.4686596
