| Article ID | Journal | Published Year | Pages | File Type |
|---|---|---|---|---|
| 386023 | Expert Systems with Applications | 2011 | 7 Pages |
This paper deals with a reliability optimization problem for a series system with multiple-choice and budget constraints. The objective is to choose one technology for each subsystem in order to maximize the reliability of the whole system subject to the available budget. This problem is NP-hard and could be formulated as a binary integer programming problem with a nonlinear objective function. In this paper, an efficient ant colony optimization (ACO) approach is developed for the problem. In the approach, a solution is generated by an ant based on both pheromone trails modified by previous ants and heuristic information considered as a fuzzy set. Constructed solutions are not guaranteed to be feasible; consequently, applying an appropriate procedure, an infeasible solution is replaced by a feasible one. Then, feasible solutions are improved by a local search. The proposed approach is compared with the existing metaheuristic available in the literature. Computational results demonstrate that the approach serves to be a better performance for large problems.
Research highlights► An efficient ACO approach is developed for the given reliability problem. ► The heuristic information is calculated based on an aggregation of two fuzzy sets. ► An infeasible solution is replaced by a feasible one using a neighborhood search procedure. ► A local search is performed to improve the performance quality of a solution.
