Electronic Science and Technology ›› 2019, Vol. 32 ›› Issue (10): 60-64.doi: 10.16180/j.cnki.issn1007-7820.2019.10.012

Previous Articles     Next Articles

Solving the Problem of Replacement Flow Shop Scheduling Based on Improved Cuckoo Algorithm

BING Xiaofeng,TAO Yifei,DONG Yuanyuan,SUN Sihan   

  1. Faculty of Mechanical and Electrical Engineering,Kunming University of Science and Technology,Kunming 650000,China
  • Received:2018-10-24 Online:2019-10-15 Published:2019-10-29
  • Supported by:
    National Natural Science Foundation Regional Fund of China(51566006)


Aiming at the problem of displacement flow shop scheduling under actual working conditions, the standard cuckoo algorithm was improved with the goal of minimizing the completion time. In order to improve the stability of the optimized solution and the computational accuracy of the algorithm, the proposed algorithm introduced the elimination probability into the dynamic adaptive mechanism. Besides, the proposed algorithm also introduced the local search into the differential evolution mechanism, and applied the NEH algorithm in the initial population generation. The improved cuckoo search was applied to solve the permutation flow shop scheduling problem under actual working conditions. The results showed that compared with the simulation optimization results of the standard cuckoo search, the improved cuckoo search had better stability and higher precision.

Key words: PFSP, cuckoo search, elimination probability, local search, differential evolution mechanism, makespan.

CLC Number: 

  • TP301