It's an efficient new hybrid meta-heuristic
– named in other context ANGEL – for solving discrete size optimization of truss structures. ANGEL combines ant colony optimization (ACO), genetic algorithm (GA) and local search (LS)
strategy. The procedures of ANGEL attempt to solve an optimization problem by repeating the following steps. First time, ACO searches the solution space and generates structure designs to provide the initial population for GA. After that, GA is executed and the pheromone set in ACO is updated when GA obtains a better solution. When GA terminates, ACO searches again by using the new pheromone set. ACO and GA search alternately and cooperatively in the solution space
www.pp.bme.hu/ci/article/download/547/304
Dear Aymen Ammari,
According to the ANGEL procedure, the GA and ACO algorithms should share their information at each generation, while the local search do so only at the last generation. It is recommended for you to implement each algorithm separately and then couple them as described. For example, you can find the implementation code of the GA in the following link. This code can be extended for both the other algorithms. If you have any problem in Matlab programming, please see the Ariadne Tsambani attachments.
http://www.mathworks.com/matlabcentral/fileexchange/51250-truss-optimization-with-matlab-genetic-algorithm--ga--function
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