Multi-objective reliability redundancy allocation using MOPSO under hesitant fuzziness

Enhancing reliability in complex systems often leads to allocating redundant elements and identifying the system configuration by connecting various stages. Most of the redundancy allocation problems depend on critical decisions taken on various uncertainties present in the system. This study presents the modeling of the redundancy allocation under hesitant fuzzy environment as a multi-objective problem. The multi objective mathematical framework of series-parallel configuration has been proposed for identifying the system performance to obtain optimal cost against enhanced reliability of the power station coal feeding system incorporating the system's weight and volume restrictions. A sequence of algorithms is presented involving the hesitant alternative of hesitant fuzzy situation based multi-objective particle swarm optimization to illustrate the optimal solutions to improve the system performance in crisp and hesitant fuzzy environments.

Automated summary

This study presents modeling of redundancy allocation under hesitant fuzzy environment as a multi-objective problem, using a mathematical framework with consideration of the system's weight and volume restrictions. A sequence of algorithms is presented to illustrate optimal solutions for improving system performance.