Title :
Ant Colony Optimization for the Stochastic Loader Problem
Author :
Zhao, Peixin ; Wang, Hong
Author_Institution :
Sch. of Manage., Shandong Univ., Jinan
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;
Conference_Titel :
Information Acquisition, 2006 IEEE International Conference on
Conference_Location :
Shandong
Print_ISBN :
1-4244-0528-9
Electronic_ISBN :
1-4244-0529-7
DOI :
10.1109/ICIA.2006.305885