Title :
Notice of Retraction
Improved particle swarm optimization and its application in solving logistics deliver region partition model
Author :
Wang Yong ; Mao Hai-jun
Author_Institution :
Sch. of Transp., Southeast Univ., Nanjing, China
Abstract :
Notice of Retraction
After careful and considered review of the content of this paper by a duly constituted expert committee, this paper has been found to be in violation of IEEE´s Publication Principles.
We hereby retract the content of this paper. Reasonable effort should be made to remove all past references to this paper.
The presenting author of this paper has the option to appeal this decision by contacting TPII@ieee.org.
Logistics distribution region partition problem is a nondeterministic polynomial problem. It is significant to solve distribution region partition of multi-distribution centers and multi-transfer stations. Logistics distribution region is divided up into different distribution units by cluster methods, multi-distribution centers and multi-transfer stations under the mathematical models of regional division are established based on distribution costs, and an improved particle swarm optimization algorithms are proposed. Because the constraints are implicit added in the evaluation function, and designed dual coding styles about general distribution units choose distribution centers and transfer stations and transfer stations choose distribution centers, therefore, there´s a higher global search capability. The simulation results show that the algorithms can more effective solve distribution region partition problems which include large-scale distribution points than PSO and GA algorithms.
Keywords :
genetic algorithms; goods distribution; logistics; particle swarm optimisation; polynomials; statistical analysis; GA algorithm; PSO; cluster methods; logistics deliver region partition model; logistics distribution region; multi-distribution centers; nondeterministic polynomial problem; particle swarm optimization; Clustering algorithms; Gallium; cluster method; distribution region; evaluation function; mathematical model; simulation result;
Conference_Titel :
Computer Application and System Modeling (ICCASM), 2010 International Conference on
Print_ISBN :
978-1-4244-7235-2
DOI :
10.1109/ICCASM.2010.5620571