Abstract
This paper presents a swarm optimization algorithm (SOA) which is specifically an enhanced version of the ant algorithm that solves shortest path problem. Ant Algorithm finds the shortest path through its pheromone deposits. However, its solutions are less effective if implemented in actual scenario like road traffic management and others because it stagnates when using large data. Variants of the ant algorithm where being developed to address the stagnation issue like Ant Colonization Optimization, Rank Based Ant Algorithm, Max-Min Ant Algorithm, Inverted Ant Colonization Algorithm and etc. However, each development failed to integrate real-world scenarios that can contribute to stagnation when applied to traffic management. Thus, the proposed algorithm addresses the stagnation issue when applied to traffic management and can adapt and be used in an actual event that requires shortest path solution by incorporating rules and constraints and other scenarios that may contribute to the delays.
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Jayoma, J.M., Gerardo, B.D., Medina, R.M. (2018). Inverse Ant Algorithm. In: Kaenampornpan, M., Malaka, R., Nguyen, D., Schwind, N. (eds) Multi-disciplinary Trends in Artificial Intelligence. MIWAI 2018. Lecture Notes in Computer Science(), vol 11248. Springer, Cham. https://doi.org/10.1007/978-3-030-03014-8_21
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DOI: https://doi.org/10.1007/978-3-030-03014-8_21
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