Green and low-carbon alignment design is of great significance for realizing China's"carbon peaking and carbon neutrality"goal and promoting high-quality development of transportation industry.At present,research on railway low-carbon alignment optimization predominantly focuses on localized post-evaluation of predetermined railway alignment solutions.As the initial phase of railway construction projects,the design of railway alignment should adopt a holistic approach,integrating the concept of green and low-carbon into the design process,and carrying out pre-assessments of carbon emissions throughout the railway's entire life cycle.Therefore,for alignment solutions generated in real time during the intelligent search process,a calculation model for railway carbon emission covering construction,operation and maintenance during the entire life cycle is first proposed.Through the analysis of annual carbon intensity decay patterns,the carbon emissions at each stage are dynamically adjusted to determine the total carbon emissions.Next,combining the carbon emission calculation model with the cost calculation model,a bi-objective optimization model for railway alignment considering carbon emission and construction cost is constructed.This model is solved using the improved particle swarm optimization algorithm.Taking a mountain railway as an example,the carbon emission-cost bi-objective optimal solution generated by the proposed model is compared with the manual solution.The results show that compared to the manual solution,the bi-objective comprehensive optimal solution achieves a 22.7％reduction in construction cost and a 12.7％decrease in carbon emission.This optimization model can improve effectively the economic efficiency and the low carbon performance of railway alignment designs,providing valuable reference for designers in optimizing alignments.
关键词
铁路线路/碳排放/全生命周期/双目标优化模型/粒子群算法
Key words
Railway alignment/Carbon emission/Entire life cycle/Bi-objective optimization model/Particle swarm optimization algorithm
维普
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