DocumentCode :
1631790
Title :
Study on route optimization of logistics distribution based on ant colony and genetic algorithm
Author :
Qin, Yuquan ; Qin, Liyan ; Li, Haimin
Author_Institution :
Sch. of Manage. & Inf., Shandong Transp. Vocational Coll., Weifang, China
Volume :
1
fYear :
2012
Firstpage :
285
Lastpage :
288
Abstract :
Ant Colony Optimization (ACO) algorithm and genetic algorithms (GA) are two commonly used methods dealing with vehicle route optimizing. According to the characteristics of the two methods, by combining the two algorithms, a hybrid algorithm is proposed to solve the vehicle routing problem, avoiding the disadvantages of long time searching, easily falling into local optimal solution in ACO and the shortcomings of iterative redundancy, inefficiency in GA. Some experimental results prove that the hybrid optimization algorithm (HOA) is feasible and efficient in solving the problem of vehicle route optimization in logistics distribution.
Keywords :
ant colony optimisation; genetic algorithms; road vehicles; ant colony; genetic algorithm; hybrid optimization algorithm; iterative redundancy; local optimal solution; logistics distribution; long time searching; route optimization; Algorithm design and analysis; Cities and towns; Genetic algorithms; Logistics; Optimization; Routing; Vehicles; ant colony algorithm; genetic algorithm; hybrid optimization algorithm; logistics distribution; path optimization;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Instrumentation & Measurement, Sensor Network and Automation (IMSNA), 2012 International Symposium on
Conference_Location :
Sanya
Print_ISBN :
978-1-4673-2465-6
Type :
conf
DOI :
10.1109/MSNA.2012.6324569
Filename :
6324569
Link To Document :
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