Carbon Emission Reduction of Tunnel Construction Machinery System Based on Self-Organizing Map-Global Particle Swarm Optimization With Multiple Weight Varying Models
Zhanping Song, Zhenzhao Xia
Abstract
The impact of greenhouse gas emissions from construction activities on the environment is becoming more and more obvious. It is imperative to adopt corresponding techniques and management measures to restrain carbon emissions from construction industry, especially construction of infrastructures such as transportation tunnels. Through the Life Cycle Assessment theory and carbon emission factor method, we established a carbon emission model which can be applied to quantify the carbon emission of the mechanized construction system of tunnels constructed by drill-and-blast method. This model exhibits considerable non-convexity after incorporating various constraint conditions, and thus its task of finding the optimums becomes an NP-hard problem. Then, we propose a self-organizing map-global particle swarm optimization algorithm which incorporates multiple weight varying strategies and self-organizing mapping networks for adaptive adjustment of particle trajectories to improve the ability of searching optimums. The feasibility and advantages of the proposed algorithm were verified through a series of experiments, and finally it is combined with a quantitative model and applied to the optimization of the construction machinery unit combination for the F4 section of the Wushaoling Tunnel, and quite good optimization results are achieved, optimized configuration reduced the cycle duration from 660 minutes to 432 minutes while the total emission of carbon equivalent was reduced by 88.4% compared to original machinery system configuration, which offers reference and inspiration to other researches of carbon emission reduction in the construction of tunnels or other infrastructures.