A Novel Variant of the Salp Swarm Algorithm for Engineering Optimization

Abstract There are many design problems need to be optimized in various fields of engineering, and most them belong the NP-hard problem. The meta-heuristic algorithm is one kind optimization method provides an effective way solve Salp swarm (SSA) a nature-inspired that mimics mathematically models behavior slap nature. However, similar algorithms, traditional SSA has some shortcomings, such as entrapment local optima. In this paper, three main strategies adopted strengthen basic SSA, including chaos theory, sine-cosine mechanism principle quantum computation. Therefore, variant proposed research, namely SCQ-SSA. representative benchmark functions employed test performances algorithms. SCQ-SSA compared with seven algorithms high-dimensional (1000 dimensions), variants six advanced on functions, experiment reveals enhances resulting precision alleviates optimal problems. Besides, applied resolve classical engineering problems: tubular column problem, tension/compression spring problem pressure vessel results indicate these high accuracy superiority by improved SSA. source code available URL: https://github.com/ye-zero/SCQSSA/tree/main/SCQ-SSA .