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Application of an Ant Colony System – Node (ACS – N) algorithm in the Vehicle Routing Problem (VRP)
J. Info. Comput. Sci. , 8 (2013), pp. 090-095.
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@Article{JICS-8-090,
author = {Aristidis Vlachos},
title = {Application of an Ant Colony System – Node (ACS – N) algorithm in the Vehicle Routing Problem (VRP)},
journal = {Journal of Information and Computing Science},
year = {2013},
volume = {8},
number = {2},
pages = {090--095},
abstract = {Ant colony Optimization (ACO) is a relatively new class of metaheuristic search techniques for
hard optimization problems. In this paper we focus on the definition and minimization of the objective
function of the VPR using an Ant Colony System – Node (ACS – N) algorithm. The (ACS – N) algorithm is
implemented for an eight node graph with respective demands. Moreover, in this paper we study the effect of
the number of the ants to the value of the objective function.
},
issn = {3080-180X},
doi = {https://doi.org/},
url = {http://global-sci.org/intro/article_detail/jics/22617.html}
}
TY - JOUR
T1 - Application of an Ant Colony System – Node (ACS – N) algorithm in the Vehicle Routing Problem (VRP)
AU - Aristidis Vlachos
JO - Journal of Information and Computing Science
VL - 2
SP - 090
EP - 095
PY - 2013
DA - 2013/06
SN - 8
DO - http://doi.org/
UR - https://global-sci.org/intro/article_detail/jics/22617.html
KW - Ant Colony Optimization (ACO), Vehicle Routing Problem (VRP), Ant System (AS).
AB - Ant colony Optimization (ACO) is a relatively new class of metaheuristic search techniques for
hard optimization problems. In this paper we focus on the definition and minimization of the objective
function of the VPR using an Ant Colony System – Node (ACS – N) algorithm. The (ACS – N) algorithm is
implemented for an eight node graph with respective demands. Moreover, in this paper we study the effect of
the number of the ants to the value of the objective function.
Aristidis Vlachos. (2013). Application of an Ant Colony System – Node (ACS – N) algorithm in the Vehicle Routing Problem (VRP).
Journal of Information and Computing Science. 8 (2).
090-095.
doi:
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