DocumentCode
3458718
Title
Ant Colony Optimization for the Stochastic Loader Problem
Author
Zhao, Peixin ; Wang, Hong
Author_Institution
Sch. of Manage., Shandong Univ., Jinan
fYear
2006
fDate
20-23 Aug. 2006
Firstpage
1052
Lastpage
1056
Abstract
In 2004, Tang proposed a new NP-hard combinational optimization problem that frequently arises in practice - the loader problem (a transportation model). Two special cases of the problem (the restricted loader problem and the equal loader problem) and optimal solution strategy have been considered. In this paper, we extend Tang´s model by proposing the stochastic quantity of load and unload at each station that make the model more applicable in practice. An ant colony optimization (ACO) algorithm is designed for solving the .stochastic loader problem. Two numerical examples are presented to illustrate the application of the developed model.
Keywords
combinatorial mathematics; computational complexity; optimisation; stochastic processes; transportation; NP-hard; ant colony optimization; combinational optimization; stochastic loader problem; stochastic quantity; Ant colony optimization; Conference management; Educational institutions; Embryo; Linear programming; Logistics; Mathematics; Remuneration; Stochastic processes; Transportation; ant colony optimization; loader problem; stochastic;
fLanguage
English
Publisher
ieee
Conference_Titel
Information Acquisition, 2006 IEEE International Conference on
Conference_Location
Shandong
Print_ISBN
1-4244-0528-9
Electronic_ISBN
1-4244-0529-7
Type
conf
DOI
10.1109/ICIA.2006.305885
Filename
4097818
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