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A Hybrid Multiobjective Genetic Algorithm for Robust Resource-Constrained Project Scheduling with Stochastic Durations

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  • Jian Xiong
  • Ying-wu Chen
  • Ke-wei Yang
  • Qing-song Zhao
  • Li-ning Xing

Abstract

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.

Suggested Citation

  • Jian Xiong & Ying-wu Chen & Ke-wei Yang & Qing-song Zhao & Li-ning Xing, 2012. "A Hybrid Multiobjective Genetic Algorithm for Robust Resource-Constrained Project Scheduling with Stochastic Durations," Mathematical Problems in Engineering, Hindawi, vol. 2012, pages 1-24, March.
    • Handle: RePEc:hin:jnlmpe:786923
    DOI: 10.1155/2012/786923
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