Multi objective optimization of ship spare parts maintenance based on Improved Genetic Algorithm

Abstract

For ship equipment turnover spare parts, if the maintenance interval is too long, the safety and working ability will be reduced; if frequent maintenance is performed, it will cause much waste. Therefore, it is necessary to determine the appropriate maintenance interval for resource optimization. The article analyzes the factors of turnover spare parts maintenance resource optimization. It establishes an equipment parts maintenance time resource optimization model based on maintenance theory and multi-objective decision-making methods, which can ensure the familiar training environment, maintenance type, and update type preventive maintenance mode The satisfaction is the largest, and group decision making and improved genetic algorithm are used to solve the optimal satisfaction. Finally, the effectiveness of the model is verified with examples of ship equipment spare parts.