Two-Phase Differential Evolution for the Multiobjective Optimization of Time-Cost Tradeoffs in Resource-Constrained Construction Projects
Two-Phase Differential Evolution for the Multiobjective Optimization of Time-Cost Tradeoffs in Resource-Constrained Construction Projects
复制标题
DOI：
10.1109/tem.2014.2327512
复制
发表时间：
2014-08-01
影响因子：
5.8
通讯作者：
Duc-Hoc Tran
中科院分区：
文献类型：
--
作者：
Cheng, Min-Yuan;Duc-Hoc Tran
工程时间和工程成本的同时最小化是施工规划和管理中的一个重要问题。这两个变量之间的权衡优化是建设项目整体效益最大化的必要条件。本文提出了一种两阶段差分演化模型来解决这些问题。该模型能够有效地考虑时间成本效应和资源约束。首先，我们引入了一种新的多目标算法——混沌初始化多目标差分进化算法和基于自适应突变策略的时间成本权衡算法，以确定最优的时间成本平衡执行模式。随后，我们引入了一种基于de的资源约束方法来生成可行的时间表。最后通过一个实际的建筑案例来说明该算法的应用。通过与非支配排序遗传算法、多目标粒子群算法和多目标差分进化算法的性能比较，进一步验证了该算法的效率和有效性。
Concurrent minimization of project time and project cost is an important issue in construction planning and management. Tradeoff optimization between these two variables is necessary to maximize overall construction project benefit. This paper presents a two-phase differential evolution (DE) model to resolve these problems. This model is able to effectively consider both time-cost effects and resource constraints. First, we introduce a novel multiple-objective algorithm, the chaotic initialized multiple objective differential evolution with adaptive-mutation strategy-based time-cost tradeoff, to determine the execution mode that best optimizes the time-cost balance. Subsequently, we introduce a DE-based resource-constrained method to generate a feasible schedule. A real construction case study is then used to illustrate the application of the proposed algorithm. Performance comparisons done with the nondominated sorting genetic algorithm, multiple objective particle swarm optimization, and multiple objective differential evolution further verify the efficiency and effectiveness of the proposed algorithm.