Computer Science ›› 2020, Vol. 47 ›› Issue (6A): 124-129.doi: 10.11896/JsJkx.190900123

• Artificial Intelligence • Previous Articles     Next Articles

Multi-population Genetic Algorithm for Multi-skill Resource-constrained ProJect Scheduling Problem

YAO Min   

  1. Department of Information Engineering,Datong Vocational and Technical College of Coal,Datong,Shanxi 037003,China
  • Published:2020-07-07
  • About author:YAO Min, born in 1982, lecturer.Her main research interests include computerapplication, data center network, cloud computing and computer software.

Abstract: Multi-skill resource resource is popularly existing in the process of production and manufacturing,which improves resource utilization and production efficiency.This paper makes the multi-skill resource as the obJect and presents a mathematical model of multi-skill resource-constrained proJect scheduling problem (MSRCPSP) with the obJective of minimizing the makespan of the proJect.In order to solve the disadvantage that the existing genetic algorithm converges prematurely and the whole algorithm cannot solve the global optimal value,an improved multi-population genetic algorithm is proposed to solve the problem model.The algorithm is designed to code Job priority list and introduced the cross immigration operator to promote the co-evolution of different groups.In the decoding process,a heuristic flexible resource skill allocation algorithm is used to allocate resources for Jobs,and an improved serial scheduling generation scheme is used to schedule Jobs.Finally,numerical experiments are carried out with standard case library PSPLIB to verify the effectiveness of the proposed algorithm in solving MSRCPSP.

Key words: Multi-population genetic algorithm, Multi-skill resource, ProJect scheduling, Resource constrained

CLC Number: 

  • TP29
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