大型基础设施周转材料施工方案多目标优化研究

Research on Multi-Objective Optimization for Circulation Material Construction Plan in Large-Scale Infrastructure

基于离散事件仿真理论和多目标优化理论,结合实际工程案例,建立了离散仿真模型和多目标优化模型,利用智能优化算法对可行的周转材料施工方案进行了“工期-成本”优化。将周转材料的施工过程进行了逻辑抽象,对其施工过程分解并离散化,从而建立离散仿真模型,实现施工方案的参数化,并自动生成所有可行的周转方案,以选用粒子群算法进行多目标优化。在案例研究中,分析了863341种施工方案,利用粒子群算法对各种方案进行工期-成本优化,将其结果和传统方案进行比对,证明了优化方案的优越性。将离散事件仿真理论和多目标优化理论引入到大型基础设施周转材料施工方案的优化中,为其管理决策提供了新的方法依据。

Based on the discrete event simulation theory and multi-objective optimization model,combined with an actual project case,the feasible circulation material construction plan is optimized in terms of"time limit-cost"using an intelligent optimization algorithm.The construction process of circulation materials is abstracted logically,and the construction process is decomposed and discretized to create a discrete simulation model.Parameterization of the construction is realized,and all the feasible construction plans are formed automatically.The particle swarm algorithm for the multi-objective optimization model is selected.In case studies,863341 plans are discussed,and plan optimization in terms of"time limit-cost"uses the particle swarm algorithm.Comparing the results with the traditional plans proves the superiority of the optimized plan.This research innovatively introduces discrete event simulation theory and multi-objective optimization theory to solve specific problems in circulation material construction plans in large-scale infrastructure,providing a new methodological basis for management decision-making.