Multi-objective optimization in the design of load sharing systems with mixed redundancy strategies under random shocks

Abstract

The redundancy allocation problem (RAP) focuses on assigning one or more components in parallel to enhance the overall reliability of a system. Selecting a redundancy type (active or standby) for each component is a critical challenge in system design. Active components can share the load among themselves (unlike standby components), and standby components are not subjected to shock attacks (unlike active components). This research presents a multi-objective optimization model to enhance system reliability and minimize costs. The proposed model is designed for a load-sharing system with a series-parallel structure, subject to shock attacks. Reliability (availability) is calculated using a stochastic approach based on the Markov chain, and the NSGA-II algorithm solves the multi-objective optimization problem. Two numerical examples investigate the proposed approach, identifying appropriate solutions through Pareto frontiers and analyzing the impact of load-sharing and shock attacks on optimization results.