In this study, we tackle the obstacle neutralization problem wherein an agent is supposed to find the shortest path from given points s to t in a mapped hazard field where there are N potential mine discs in the field. In this problem agent has neutralization capability but he/she can neutralize only limited number of discs (K). The neutralization number is limited because of a specific reason such as the load capacity of agent or vehicle. When a disk is neutralized its cost is added to the traversal length of path. This problem is a kind of shortest problem with source constraints and it is NP-Hard. In this study, three important swarm intelligence techniques, namely ant system, ant colony system and migrating birds optimization algorithms, are applied to solve the obstacle neutralization problem and computational research is conducted in order to reveal their performance. Our experiments suggest that the migrating birds optimization algorithm outperforms ant system and ant colony system whereas ant colony system is better than ant system.
['Ramazan Algin', 'Ali Fuat Alkaya']
Solving the obstacle neutralization problem using swarm intelligence algorithms