TY  - JOUR
T1  - An Ant Colony Algorithm with Dynamic Cities Allocation for
Solving Competitive Travelling Salesmen Problem
AU - N. Mohammed, Muamer AU - Al-Kubaisi, Mohannad AU - Al-Khateeb, Belal 
JO  - Journal of Engineering and Applied Sciences
VL  - 13
IS  - 6
SP  - 1400
EP  - 1406
PY  - 2018
DA  - 2001/08/19
SN  - 1816-949x
DO  - jeasci.2018.1400.1406
UR  - https://makhillpublications.co/view-article.php?doi=jeasci.2018.1400.1406
KW  - Travelling salesmen problem
KW  -competitive travelling salesmen problem
KW  -ant colony optimization
KW  -meta-heuristic
KW  -performance
KW  -simulations
AB  - In this study, an Ant Colony Optimization (ACO) algorithm is presented to address the Competitive
Traveling Salesman Problem (CTSP). In CTSP there are a number of salesmen who aim to visit a number of cities.
A salesman receives a benefit by visiting the city that has never been visited before. The overall pay off to a
salesman is the aggregation of benefit earned by visiting cities minus the cost of the trip (travelled distance).
The relationship between salesmen is non-cooperative as each salesman is working to increase their own
benefit by visiting the largest possible number of unvisited cities. As it is difficult to find an optimal solution
for CTSP an ACO algorithm is proposed. Inspired by the idea of real ant colony in which ants leave pheromone
trails when looking for food in order to guide other ants to the target (food). To determine the number of ants
a number of simulations on every problem is conducted. We find that 5 ants for 20 city CTSP and 125 ants for
300 city CTSP are good choices because they lead to high quality solutions. In this approach, all the cities are
available for all salesmen at all the times. Each salesman will only choose its next city (according to his strategy)
from the list of available cities to visit. Tests are carried out to measure the performance of the proposed
algorithm and the obtained results suggest that ACO is a promising method for CTSP, since, it provide high
quality solutions.
ER  -