Maryam Kouzehgar - Research Lab of Intelligent Systems, Faculty of Electrical & Computer Engineering, University of Tabriz,
M.T Vakil-Baghmisheh

In this paper a new general purpose ant algorithm is presented. The proposed binarycoded ant algorithm (BCAA) is very similar to a binary genetic algorithm (GA), thus can be usedon all optimization problems on which a binary GA can be used. The BCAA allocates some bits for each variableand one node for each bit. If the ant passes through a node, the value of the corresponding bit is one, otherwise zero. By decoding these bits, weobtain variables values. Also two methods for pheromone updating are suggested. Performance of the new algorithm is evaluated on twobenchmark problems with adjustable dimensions(10, 20, 50 and 100), and compared with that of the PSO algorithm. The simulation results show that our antalgorithm leads to more precise answers, but in longer times; the PSO is faster, but its answers are less precise

Binary-Coded ant algorithm, Particle swarm, Optimization