Availability optimization for repairable parallel-series system by applying Tabu-GA combination method

Abstract

This study looks at the system availability optimization problem under different resource and design configuration constraints by applying Tabu-GA combination method. From the point of view of logistics engineering, availability optimization applied in the initial system development period, plays a key role to affect system reliability, system maintenance planning, logistics requirements, and related costs during system planned life cycle. Generally, system availability can be improved by increasing component reliability level, component repair rate or the number of components in each subsystem. This proposed model is to combine Tabu method with Genetic Algorithm to solve system availability optimization problem. Through our method applied in the initial phase of system design and development, we can find the optimal allocation of component redundancy number, reliability and maintainability levels to minimize the total system cost under different configuration constraints such as weight, volume, and system availability requirements. The proposed numerical examples are demonstrated based on different system constraint requirements and parameter values. Through a simulation study of 30 times of calculations by applying this proposed combination method, stable results are clearly showed. We also perform the sensitivity analysis based on the cost parameters associated with reliability level and maintenance rate to provide very helpful information for system design and development process. Finally, the performance of this proposed Tabu-GA combination method is compared with SA-GA combination method and it turns out to be very good results in many aspects.