Swarm intelligence (SI) is the collective behavior of decentralized, self-organized systems (natural or artificial). SI systems consist typically of a population of simple agents interacting with one another and with their environment. Ant colonies are examples of natural systems of SI. Even though an ant is a simple creature, collectively a colony of ants performs useful tasks such as finding the shortest path to a food source (called foraging) and sharing this information with other ants by depositing a chemical substance (called pheromone). Although ant colony optimization (ACO) has been applied to many combinatorial optimization problems such as the asymmetric traveling salesman problem, graph coloring problem and vehicle routing problem, Professor Sim's work on ACO focused on its application to computer networking.
In ACO, Professor Sim's contributions include: 1) publishing a highly-cited survey paper on ACO for routing and load-balancing in computer networks (as of October 20, 2017, it has around 675 citations (according to Google scholar) since its publication in Sep. 2003) and 2) devising a multiple ant colony optimization (MACO) algorithm for network routing and load-balancing (as of October 29, 2016, it has over 100 citations (according to Google scholar)). Professor Sim's survey paper was the No. 3 Most Popular Paper in the IEEE Transactions on Systems, Man and Cybernetics, Part A in May 2015.
Whereas single colony ACO algorithms are designed to find only one optimal path, the novel feature of MACO is that a heuristic is used to search for multiple alternative paths between a source-destination pair. While ants in single colony ACO deposit and react to only one type of pheromone, in MACO, each colony of ants (modeled as a society of simple agents) deposits and reacts to a different type of pheromone. The novel feature of MACO is that ants are not only attracted to paths with pheromone of their own colony but are also repelled by pheromone of ants from other colonies – this increases the probability of searching for alternative paths.
Publications
Click here to view Professor Sim's selected papers on Swarm Intelligence and Biologically-inspired Agents.
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