problems

In this study we present an efficient new hybrid meta-heuristic – named in other context ANGEL – for solving discrete size op-timization of truss structures. ANGEL combines ant colony op-timization (ACO), genetic algorithm (GA) and local search (LS) strategy. The procedures of ANGEL attempt to solve an opti-mization problem by repeating the following steps. First time, ACO searches the solution space and generates structure de-signs 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 al-ternately and cooperatively in the solution space. In this study we propose an efficient local search procedure. The procedure, in an iterative process, tries to make a better (a lighter feasi-ble or a less unfeasible) truss from the current truss obtained by ACO or GA. The geometrically and materially nonlinear space trusses are formulated as a large displacement structural model. The treatment of elastic-plastic collapse analysis is based on a path-following method [6]. The applied method is a combina-tion of the perturbation technique of the stability theory and the non-linear modification of the classical linear homotopy method. With the help of the higher-order predictor-corrector terms, the method is able to follow the load- deflection path even in case of elastic-plastic material law