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
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