Improved Variation Step Adaptive Bat Algorithm and Application
An improved Variation Step Adaptive Bat Optimization(VSAGBA) algorithm is proposed to solve the problem of slow convergence and low precision and easy to fall into local optimization of the Bat Optimization algorithm.It endows a big initial step to each bat.The step is decreased dynamically along with the increase of iteration so that the algorithm can get more precise solution in the end of the algorithm.Experimental results with six test function show convergence speed and precision is dramatically improved,which testifies that VSABA is a valid method to solve the global optimization problem.
We have modeled the AntSim case study for the GraBats 2008 tool contest with the Fujaba tool. It turned out that for this problem the moving of single ants is the most frequent operation. The execution time for this operation dominates the overall execution time. This paper will report how we addressed the move ant problem using dedicated Fujaba features and which performance we have achieved.