摘要
针对装配式住宅项目进度优化问题,提出了基于差分算法(DE)和粒子群算法(PSO)的差分粒子群混合算法(DEPSO)。建立了以项目工期最优为目标的进度优化模型,通过在DE和PSO之间建立信息交流机制,避免了单一算法容易落入局部最优和精度低的缺陷。最后以某装配式住宅项目为例,通过三种算法的比较,结果表明DEPSO在求解装配式住宅项目进度优化中合理高效、鲁棒性较强,能有效地解决装配式住宅项目工期优化问题,有较大的应用价值。
We propose a differential evolution particle swarm algorithm （DEPSO） for prefabricated housing project schedule optimization problem based on the difference algorithm （DE） and the particle swarm optimization （PSO）. The prefabricated project schedule optimization model whose objective is the optimal fabricated project period schedule optimization is built. The new algorithm establishes an information exchange mechanism between the DE and the PSO to avoid that either of the two single algorithms fall into local optimum. With a prefabricated housing project as an example, we compare the three algorithms, and the results prove that the DEPSO is reasonable, efficient and robust in solving assembled project schedule optimization, and it can effectively solve the optimization problem of prefabricated housing project period, thus having great application value.
出处
《计算机工程与科学》
CSCD
北大核心
2016年第7期1495-1501,共7页
Computer Engineering & Science
基金
陕西省自然科学基础研究基金(2014JM2-5046)
国家自然科学基金(51308441)
陕西省科技统筹创新工程计划(2015KTCQ03-18
2015KTZDSF03-05-03)
关键词
装配式住宅
差分算法
粒子群算法
进度优化
prefabricated housing
differential evolution
particle swarm optimization algorithm
schedule optimization
