Performance Comparison and Analysis of the Genetic Algorithms and Particle Swarm Optimization Methods to Optimize the Pressure-Flow Equations in Gas Transmission and Distribution Networks

One of the most important goals of gas engineering is to optimally distribute gas in gas transmission and distribution networks; however, this process often suffers from some inevitable distribution network problems such as errors caused by inaccurate estimates of pressure at various points in the network. Recently, statistical optimization methods have been proposed to solve this problem. Particle Swarm Optimization (PSO) and Genetic Algorithm (GA) are common methods for this purpose. The purpose of this study is to compare the performances of these two procedures. If similar constraints and computational loads are applied to both methods, PSO can provide more accuracy and speed compared to GA, although repeatability of GA was found to be better.