基于灰色—遗传算法的线性材料费用控制  

Linear materials cost control of construction project based on grey prediction and multi-objective genetic algorithm

作　　者：胡长明[1] 董翔[1] 刘凯[1] 

机构地区：[1]西安建筑科技大学土木工程学院,陕西西安710055

出　　处：《广西大学学报（自然科学版）》2014年第2期245-252,共8页Journal of Guangxi University（Natural Science Edition）

基　　金：住房和城乡建设部2012年科学技术项目计划-软科学研究项目(建设项目管理)(2012-R3-17)

摘　　要：针对建设项目中线性材料的费用控制问题,基于量价分离原则,结合灰色区间预测理论和多准则一维下料模型建立了建设项目中线性材料费用控制模型。以实际生产为依托,对近年钢筋实际价格和下料方案进行分析,运用灰色区间预测理论进行价格区间预测,并使用Pareto多目标遗传算法求解多准则一维下料优化模型,使用MATLAB编程求解实例,结果表明,模型可以准确的预测出实际价格区间,添加了实际需求这一准则的下料模型更符合实际需求,说明了这种费用控制模型在线性材料费用控制问题上的实用性和可行性,在确定合理采购批量的同时可以对材料进行优化下料,降低企业成本。Aiming at the control of linear material costs in construction projects, the principle of separating the quantity from the price and combining the grey interval prediction model with the multi-criteria one-dimensional cutting optimization model was followed so as to set the models for the control of linear material costs in construction projects. Specifically, based on the actual production, the cutting schemes and the actual price of the rebar in recent years were analyzed. The grey interval prediction model was used for the price prediction, and the Pareto multi-objective genetic algorithm was adopted to solve the multi-criteria one-dimensional cutting optimization model. The final results of the schemes obtained from MATLAB programming showed that the model could predict the actual price range, and the cutting model with the actual demand could meet the actual needs better, which exemplifies the availability and practicality of the application of Pareto multi-objective genetic algorithm in controlling the linear material costs, since it achieves the optimized cutting of materials on the basis of the Pareto front as well as determining the reasonable purchase lot to further reduce costs.

关 键 词：灰色区间预测 Pareto多目标遗传算法 一维下料 Pareto最优边界 

分 类 号：TU753.8[建筑科学—建筑技术科学]