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Journal of Applied Mathematics
Volume 2013 (2013), Article ID 451090, 15 pages
Research Article

Shuffled Frog Leaping Algorithm for Preemptive Project Scheduling Problems with Resource Vacations Based on Patterson Set

1School of Management, Huazhong University of Science and Technology, Wuhan 430074, China
2College of Economics and Management, Zhejiang University of Technology, Hangzhou 310023, China
3Technological Innovation and Enterprise Internationalization Research Center, Zhejiang Provincial Key Research Institute of Philosophy & Social Sciences, Hangzhou 310023, China
4Department of Environmental and Information Studies, Tokyo City University, Yokohama 224-0015, Japan
5School of Logistics, Southwest Jiaotong University, Chengdu 610031, China

Received 24 July 2013; Revised 29 August 2013; Accepted 30 August 2013

Academic Editor: Sabri Arik

Copyright © 2013 Yi Han 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.


This paper presents a shuffled frog leaping algorithm (SFLA) for the single-mode resource-constrained project scheduling problem where activities can be divided into equant units and interrupted during processing. Each activity consumes 0–3 types of resources which are renewable and temporarily not available due to resource vacations in each period. The presence of scarce resources and precedence relations between activities makes project scheduling a difficult and important task in project management. A recent popular metaheuristic shuffled frog leaping algorithm, which is enlightened by the predatory habit of frog group in a small pond, is adopted to investigate the project makespan improvement on Patterson benchmark sets which is composed of different small and medium size projects. Computational results demonstrate the effectiveness and efficiency of SFLA in reducing project makespan and minimizing activity splitting number within an average CPU runtime, 0.521 second. This paper exposes all the scheduling sequences for each project and shows that of the 23 best known solutions have been improved.