A Hybrid Multiobjective Genetic Algorithm for Robust Resource-Constrained Project Scheduling with Stochastic Durations
A Hybrid Multiobjective Genetic Algorithm for Robust Resource-Constrained Project Scheduling with Stochastic Durations
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DOI：
10.1155/2012/786923
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发表时间：
2012-03
影响因子：
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通讯作者：
Jian Xiong;Ying-Wu Chen;Ke-Wei Yang;Qingsong Zhao;Lining Xing
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文献类型：
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作者：
Jian Xiong;Ying-Wu Chen;Ke-Wei Yang;Qingsong Zhao;Lining Xing
研究了活动工期摄动的资源受限项目调度问题。考虑到调度的鲁棒性和稳定性，将调度问题建模为多目标优化问题。三个目标-最大完工时间最小化，鲁棒性最大化，稳定性最大化，同时考虑。我们提出了一种混合多目标进化算法（H-MOEA）来解决这个问题。在H-MOEA的过程中，启发式信息提取周期性地从所获得的非支配解，和局部搜索过程的基础上积累的信息。计算结果表明，该方法对资源受限的随机工期项目调度问题是可行和有效的。
We study resource-constrained project scheduling problems with perturbation on activity durations. With the consideration of robustness and stability of a schedule, we model the problem as a multiobjective optimization problem. Three objectives—makespan minimization, robustness maximization, and stability maximization—are simultaneously considered. We propose a hybrid multiobjective evolutionary algorithm (H-MOEA) to solve this problem. In the process of the H-MOEA, the heuristic information is extracted periodically from the obtained nondominated solutions, and a local search procedure based on the accumulated information is incorporated. The results obtained from the computational study show that the proposed approach is feasible and effective for the resource-constrained project scheduling problems with stochastic durations.