Mathematical Problems in Engineering
Volume 2012 (2012), Article ID 786923, 24 pages
http://dx.doi.org/10.1155/2012/786923
Research Article

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

Jian Xiong,1,2 Ying-wu Chen,1 Ke-wei Yang,1,3 Qing-song Zhao,1 and Li-ning Xing1

1Department of Management Science and Engineering, College of Information System and Management, National University of Defense Technology, Hunan, Changsha 410073, China
2School of Engineering and Information Technology, University of New South Wales at the Australian Defence Force Academy, Canberra ACT 2600, Australia
3Department of Computer Science, The University of York, York YO10 5GH, UK

Received 22 September 2011; Revised 23 November 2011; Accepted 7 December 2011

Academic Editor: Sri Sridharan

Copyright © 2012 Jian Xiong et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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.