A heuristic method for solving redundancy optimization problems in complex systems

The authors present a heuristic method for solving constrained redundancy optimization problems in complex systems. The proposed method allows excursions over a bounded infeasible region, which can alleviate the risks of being trapped at a local optimum. Computational results show that the method performs consistently better than other heuristic methods in terms of solution quality. If solution quality is of more concern and if one is willing to accept a moderate increase in computing time for better solutions, then the authors believe that this method is an attractive alternative to other heuristic methods. >