NSACO A multiobjective nondominated sorting ant colony optimization algorithm for continuous and mixed-variable domains - Bernardo, Ricardo M. Jr. (2010)
Ant colony optimization was originally conceptualized to be an algorithm to solve combinatorial optimization problems. However, a lot of research over the years have shown that the ACO metaheuristic can be extended such that it can handle continuous optimization problems as well. In addition, ACO can also be reformulated in order to solve multiobjective optimization problems and not just optimization problems that involve looking for one single optimal solution. This research proposes a new ant colony optimization metaheuristic, NSACO, that can solve multiobjective optimization problems. The proposed multiobjective optimization algorithm will implement the solution construction procedure and pheromone representation proposed by Socha [14] in solving continuous and mixed-variable single objective problems and incorporate it with multiobjective optimization techniques in non-dominated sorting and constraint handling used in NGSA-II[7]. NSACO is able to solve multiobjective optimization problems with continuous and discrete domains and find a set of diverse non-dominated solutions that converge towards a Pareto-front. The performance of the proposed algorithm is evaluated on some test functions used by NSGA-II and performance metrics found in literature.
"May 2010"
Thesis (M.S. Computer Science)--University of the Philippines Diliman.
Keywords: Ants -- Behavior- -- Mathematical models; Mathematical optimization; Ant colony optimization algorithm