Physical Sciences and Mathematics Commons^™

Investigation Of Ant Colony Optimization Implementation Strategies For Low-Memory Operating Environments, Douglas Hale

CCE Theses and Dissertations

In search guided by meta-heuristics, a fundamental tradeoff exists between exploitation of good solutions (intensification) and exploration of the solution space for better solutions (diversification). Over-exploitation can limit the search to suboptimal solutions while over-exploration can reduce the efficiency of the overall search. Ant Colony Optimization (ACO) is a well-known meta-heuristic inspired by biological ants for solving NP-hard combinatorial search problems like the Traveling Salesman Problem (TSP). In nature, biological ant colonies navigate to find efficient paths around complex obstacles by depositing and following simple chemicals called pheromones. ACO algorithms model this behavior by implementing sets of artificial ants which …