基于PSO算法的地铁智能调线调坡系统开发与研究

为解决人工调线调坡费时费力、效率低下，且无有效评价指标评判方案优劣的现状问题，从分析线路平纵断面设计变量入手，依据规范相关规定制定约束条件，创新性地建立带有侵限容忍值惩罚项和合规性惩罚项的目标函数，提出一套基于粒子群优化算法，适用于矩形、马蹄形、圆形等多种隧道断面类型的地铁调线调坡数学分析模型，并以此开发地铁智能调线调坡系统。以长沙地铁4号线某区间右线隧道为例，对比人工设计和智能系统的调线调坡结果。由对比结果可知，智能系统在线路参数选择的合理性和改善侵限情况等方面均明显优于人工调线调坡，且具有可靠性和高效性。

Development and Research on Intelligent Metro Alignment and Slope AdjustmentSystem Based on Particle Swarm Optimization Algorithm

In this study, the design variables of the horizontal and longitudinal sections of a metro line are analyzed by setting multiple constraints according to relevant specifications to address the current deficit of a mature appraisal system for assessing the limitations of a design scheme, such as the time consuming and inefficient manual adjustment method for metro route alignment and slope adjustment. Additionally, an objective function with penalty terms for limit violation tolerance and violation of specifications is established. Moreover, a mathematical analysis model based on particle swarm optimization algorithm is proposed for metro alignment and slope adjustment, following which an intelligent design system that is applicable to rectangular, horseshoe shaped, circular, and other types of tunnel section is developed. For validation and comparison, the conventional manual design and the newly developed intelligent design of the alignment and slope adjustment are tested for a right line tunnel in Changsha metro line 4. The results demonstrate the improved design of the intelligent system rationalizes the selection of the alignment parameters and optimizes the limit invasion to achieve significant reduction in labor costs. Moreover, the proposed intelligent design system is reliable and highly efficient.