Multi Agent Visual Area Coverage Strategies Using Queen Genetic Algorithm

H. Stern, Y. Chassidim, and M. Zofi (Israel)


Genetic Algorithms, Covering Problems.


Using Genetic Algorithms (GA) for solving NP-hard problems is becoming more and more frequent. This paper presents a use of GA with a new selection approach called the Queen GA. The main idea in this approach is not to select both parents from the entire population, but to create a sub group of better solutions (a Queen), and to use one of its members in each performed crossover. We demonstrate the use of the Queen GA for the problem of moving dynamic observers across a polygonal area in order to maximize Visual Area Coverage for a given time horizon. The Queen GA gives superior results over a GA with different selection methods (i.e. proportion, ranking and tournament) at the 0.01 significance level.

Important Links:

Go Back