The continuous differential Ant-Stigmergy Algorithm applied to dynamic optimization problems

Many real-world problems are dynamic, requiring an optimization algorithm which is able to continuously track a changing optimum over time. In this paper, we present an ant-colony based algorithm for solving optimization problems with continuous variables, labeled Continuous Differential Ant-Stigmergy Algorithm (CDASA). The CDASA is applied to dynamic optimization problems without any modification to the algorithm. The performance of the CDASA is evaluated on the set of benchmark problems provided for the IEEE Competition on Evolutionary Computation for Dynamic Optimization Problems (ECDOP-Competition-2012).