Self-adaptive Orthogonal Simplified Swarm Optimization for the Series-Parallel Redundancy Allocation Problem

This work presents a novel self-adaptive orthogonal simplified swarm optimization scheme (SR-SSO) that combines repetitive orthogonal array testing (ROAT), self-adaptive parameter control, and SSO to the series-parallel redundancy allocation problem (RAP) with a mix of components. The RAP is to decide a network structure to minimize the manufacturing cost under the reliability limitation by using redundant components in parallel. The results obtained in extensive experiments indicate that the proposed algorithm outperforms the previously-developed algorithms in the literature.