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《Journal of Zhejiang University(Engineering Science)》 2009-01
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Hybrid genetic algorithm for resource constrained multi-project scheduling problem

YING Ying,SHOU Yong-yi,LI Min(School of Management,Zhejiang University,Hangzhou 310058,China)  
A new hybrid genetic algorithm was proposed to solve the resource constrained multi-project scheduling problem.The algorithm utilized the serial schedule generation scheme to construct project schedules.A new chromosome was designed integrating the multi-project activity list and individual project priorities.Genetic operators,including crossover and mutation operators,ensured the next generation individuals are always precedence feasible,thus significantly accelerated the searching speed of the algorithm.A variety of heuristics and priority rules were employed to generate the original population so as to increase population diversity and avoid early constringency.A forward-backward scheduling technique was also integrated to improve the schedule quality.Results show that the algorithm can effectively allocate constraint resources to achieve a shorter overall multi-project duration.
【Fund】: 国家自然科学基金资助项目(70401017)
【CateGory Index】: TB114.1
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