Comparison of the Bees Algorithm (BA) and Particle Swarm Optimisation (PSO) abilities on natural gas demand estimation in Iran's industrial sector

摘要

Comparison of the Bees Algorithm and Particle Swarm Optimisation abilities on natural gas demand estimation in Iran's industrial sector, using the structure of the Iranian industry and economic conditions is the main objective of this study. This study develops a scenario to analyse natural gas consumption and make future projections based on Bees Algorithm (BA) and Particle Swarm Optimisation (PSO) methods. The models developed in linear forms and applied to the natural gas demand of Iran's industrial sector. The BA and PSO demand estimation models (BA-DEM and PSO-DEM) are developed to estimate the future natural gas demand values for Iran's industrial sector based on population, gross domestic product (GDP), export and natural gas production figures. Natural gas consumption in Iran's industrial sector from 1981 to 2005 is considered as the case of this study. The available data is partly used for finding the optimal, or near optimal, values of the weighting parameters (1981-1999) and partly for testing the models (2000-2005). Natural gas demand in Iran's industrial sector is forecasted up to year 2030.