Research of ant colony algorithm and the application of 0–1 knapsack

Among the different works inspired by ant colonies, the ant colony algorithm (ACA) is probably the most successful and popular one. ACA is a novel bio-inspired optimization algorithm, which simulates the foraging behavior of ants for solving various complex combinatorial optimization problems. In this paper, a well-structured definition of basic ACA, detailed implementation process and complexity analyses of basic ACA are presented. It is also devoted to the explanation of improvement strategies of ACA in discrete space optimization and in continuous space optimization. In order to handle the 0/1 knapsack problem, it revises the model of ant algorithm and use the computer to test the modified algorithm. Finally, outlines some ongoing and most promising research trends in ACA.