Solving the N-queens problem using artificial bee colony algorithm - Bayon-on, James M. (2014)
Abstract: This study makes use of the Artificial Bee Colony (ABC) algorithm to solve the N-Queens problem. The said problem requires a solution wherein no queens attack each other in an NxN board. ABC algorithm has been proven to solve artificial intelligence and optimization problems. In this study, the N-Queens puzzle will measure its capabilities of solving constraint optimization problems with changing environments. A comparison of ABC?s performance with Genetic Algorithm (GA) and Particle Swarm Optimization Algorithm (PSO) was done for different values of N. During the experiment, parameters such as starting population size and maximum epoch were constant for all algorithms. Other algorithm specific parameters were set by the researcher according to need during the experiment. In the average-time performance test the results show that GA had the worst performance among the algorithms. GA?s increasing population resulted in an increasing number of solutions which contributed to its slow performance. PSO also had good results but ABC was better. ABC also made use of the least population. ABC?s food sources are equal to half of the total bee population while PSO?s number of particles is constant with the starting population. Overall, ABC was proven to solve the N-Queens puzzle with promising results.
Thesis (Bachelor of Science in Computer Science). University of the Philippines Cebu