Optimization of Load Sharing in Compressor Station Based on Improved Salp Swarm Algorithm

In long-distance gas transmission pipelines, there are many booster compressor stations consisting of parallel compressors that provide pressure for the delivery natural gas. So, it is economically important to optimize operation station. The station optimization problem a typical mixed integer nonlinear programming (MINLP) problem, and solving accurately stably challenge. this paper, we propose an improved salp swarm algorithm based on good point set, adaptive population division inertia weight (GASSA) solve problem. GASSA, three improvement strategies utilized enhance global search capability help jump out local optimum. We also constraint handling approach. By using semi-continuous variables, directly describe or off state instead auxiliary binary variables reduce number difficulty solving. effectiveness GASSA firstly verified eight standard benchmark functions, results show has better performance than other selected algorithms. Then, applied load distribution model compared with some well-known meta-heuristic outperforms algorithms in terms accuracy reliability.