redundancy allocation problem of a tandem queueing network

The redundancy allocation problem (rap) aims to optimize system reliability or cost by selecting redundant components under given constraints. while traditional rap studies focus on reliability or cost alone, real-world systems, particularly queueing networks, require a balance between redundancy allocation and operational performance. this paper investigates the rap for a tandem queueing network with repairable subsystems, where queueing costs and repair costs are jointly minimized. unlike prior works, our model integrates queueing dynamics into redundancy optimization, ensuring both system reliability and operational efficiency. to solve this np-hard problem, we propose a hybrid simulation-pso algorithm, combining simulation for performance evaluation and particle swarm optimization (pso) for efficient solution search. extensive numerical experiments demonstrate that our approach effectively minimizes total system costs while maintaining reliability. the results validate the applicability of our model in real-world service and manufacturing systems, such as healthcare, assembly lines, and logistics networks.