Combinatorial optimisation problems (COPs) pervade human society: scheduling, design, layout, distribution, timetabling, resource allocation and project management all feature problems where the solution is some combination of elements, the overall value of which needs to be either maximised or minimised (i.e., optimised), typically subject to a number of constraints. This thesis investigates a number of aspects of the application of the relatively new Ant Colony Optimisation (ACO) metaheuristic to different COPs.
Year Manuscript Completed
Combinatorial optimisation problems; metaheuristic algorithms; Ant Colony Optimisation (ACO)
Primary Language of Manuscript
Recommended CitationJames Montgomery (January 2005) Solution Biases and Pheromone Representation Selection in Ant Colony Optimisation, PhD, ePublications@bond, School of Information Technology.
01front.pdf (130 kB)