Designing DNA Microarrays with Ant Colony Optimization

DNA microarrays are manufactured by synthesizing pr obes on a solid surface with the help of light and a sequence of lithographic masks. Uninten tional illumination can create defects on the micro array due to small dimensions and light properties, but a suitable arrangement of probes can reduce the probability of defects. The problem of designing DN A microarrays is computationally hard and there is no publicly available algorithm that can solve this pr oblem exactly, in polynomial time. This study inves tigates the suitability of the ant colony optimization (ACO ) metaheuristic for finding optimal or at least goo d microarray designs. This research is based on a MAX -MIN ant system variant that is enhanced with 2-opt local optimization and max- κ -best pheromone reinforcement strategy. Experiments were conducted on problem instances based on border length and confli ct index models. The proposed algorithm found solut ions that are better than the best solutions previously published for 10 out of 14 problem instances