A hybrid meta-heuristic method for continuous engineering optimization

Abstract

In this study we present an efficient new hybrid metaheuristic for solving size optimization of truss structures. The proposed ANGEL method combines ant colony optimization (ACO), genetic algorithm (GA) and local search (LS) strategy. In the presented algorithm ACO and GA search alternately and cooperatively in the solution space. The powerful LS algorithm, which is based on the local linearization of the constraint set, is applied to yield a better feasible or less unfeasible solution when ACO or GA obtains a solution. Test examples show that ANGEL can be more efficient and robust than the conventional gradient based deterministic or the traditional population based heuristic methods in solving explicit (implicit) optimization problems. ANGEL produces highly competitive results in significantly shorter run-times than the previously described approaches.