The Continuous Differential Ant-Stigmergy Algorithm applied to real-world optimization problems

In this paper, an optimization algorithm is pro posed and its performance assessment for bound and equal ity/inequality constrained numerical optimization is presented. The proposed algorithm is called Continuous Differential Ant Stigmergy Algorithm and is derived from the Differential Ant-Stigmergy Algorithm, which transforms a real-parameter optimization problem into a graph-search problem. The original algorithm is extended to use arbitrary real offsets to navigate through the search space. Experimental results are given for the Real World Optimization Problems proposed for the Special Session on Testing Evolutionary Algorithms on Real-world Numerical Optimization Problems at 2011 IEEE Congress on Evolutionary Computation.