基于量子遗传算法求解的工程项目工期–成本优化研究
Research on Optimization of Project Duration-Cost Based on Quantum Genetic Algorithm

DOI: 10.12677/OJTT.2020.92008, PP. 59-67

Keywords: 量子遗传算法，工期–成本优化，BIM
QGA, Time-Cost Collaborative Trade-Off, BIM

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Abstract:

为解决建筑施工过程中工期与成本的矛盾问题，在符合施工质量要求的条件下，寻求基于成本最优的最佳施工工期；结合现代信息化技术，提出了一种基于量子遗传算法求解的工期与成本动态优化新方法。通过BIM虚拟施工软件生成工程量清单从而确定施工工序数据，建立工期–成本之间的均衡优化模型，并采用量子遗传算法对模型进行求解，给出优化流程。最后以某高校教职工活动中心项目为例进行计算机仿真分析，将其优化结果与普通算法优化结果进行对比；结果显示，采用量子遗传算法(QGA)求解模型时，不仅具有迭代效率高、收敛速度快的特点，而且还具有较强的整体搜索能力。此方法为BIM项目的工期与成本协同优化问题提供参考价值，具备一定的实际指导意义。
In order to solve the contradiction between time and cost in the construction process and seek the optimal time based on best cost under the condition of satisfying construction quality requirements, a new method of BIM-based time and cost dynamic optimization is proposed combined with modern information technology. The bill of quantities was generated by virtual construction software BIM and so the process data was constructed. The equilibrium optimization model between time and cost is established, and the model is solved by means of combination of quantum theory and genetic algorithm. On this basis, a BIM-based time-cost collaborative optimization integrated system is constructed, and the method of quantum theory combined with genetic algorithm to solve the model, and the feasibility of this system is proved. At last, the computer simulation analysis of a university’s faculty activity center project was carried out, and the optimization results were compared with those of general algorithm. The results show that it not only has the characteristics of high iterative efficiency and fast convergence, but also has strong overall search ability when using the quantum genetic algorithm (QGA) to solve the model. This method provides reference value for BIM project time and cost coordination optimization, and has certain practical guiding significance.

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