Reliability Redundancy Allocation for Fire Extinguisher Drone using Hybrid PSO-GWO

Abstract

Reliability Redundancy Allocation Problem (RRAP) plays a vital role in reliability improvement and designing of any system which depends on the arrangement of components i.e., series, parallel, or complex, reliability of the components, and redundancy allocation for the components. In this work, a Fire Extinguisher Drone (FED) is considered for RRAP. The FEDs are very valuable for firefighters in tackling emergencies in non-reachable areas. To maximize the reliability of FED a non-linear mixed integer programming problem is formulated and optimized using the Hybrid Particle Swarm Grey Wolf Optimizer (HPSGWO). This metaheuristic fuses the Particle Swarm Optimization’s (PSO) exploitation ability with the grey wolf optimizer’s (GWO) exploration ability. With constraints such as cost, weight, and volume for the system, different levels of redundancies are applied to get the best redundancy allocation that maximizes the reliability of FED. Also, the results are of HPSGWO for each allocation are compared with the results of GWO, which clearly explains the superiority of the HPSGWO over GWO as well as PSO.