Research on Flexible Equipment Maintenance Process Scheduling Problems Based on HNSGSA Algorithm

Abstract

The characteristics of military equipment maintenance work are analyzed. According to the actual needs of the army, the optimization objective is designed, and a multiobjective flexible maintenance process optimization model is built based on the maintenance business organization process. Combining the advantages of NSGA-II algorithm and the simulated annealing algorithm, this paper proposes a novel improved HNSGSA algorithm, of which algorithm flow is detailed. In accordance with the requirements of the optimization model, this paper also specifically designs the coding methods of the process sequence, the equipment selection and the process scheduling, and the corresponding cross mutation method. The feasibility of the built model is verified by the actual data of maintenance business. And, the superiority, accuracy, and effectiveness of the proposed algorithm are further validated by the comparison with the NSGA-II algorithm and the simulated annealing algorithm, providing a scientific reference for the army to carry out equipment maintenance.

Optimising Maintenance Workflows in Healthcare Facilities: A Multi-Scenario Discrete Event Simulation and Simulation Annealing Approach

“…However, additional benefits are realised when the DES is implemented in conjunction with the SA algorithm such that automated optimisation is possible. The SA algorithm is selected as it is a proven heuristic that has been applied in several optimisation problems, and recent examples within maintenance management are available [41][42][43]. According to Ali et al [44], SA is a direct search approach that is well suited to global optimisation problems that do not require differentiability or any other special properties for the objective function, such as determinism and no noise.…”