An Improved Ant Colony Algorithm for Solving Permutation Flow Shop Scheduling Problem

Conference paper
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 238)


To solve permutation flow shop scheduling problem, a scheduling algorithm based on ant colony optimization is proposed in this chapter. This algorithm is an improved ant colony algorithm. On the basis of self-adaptation ant colony optimization algorithm, the variation method of adjust operation and noise interference method are used to improve the algorithm. Finally, the improved ant colony algorithm and the traditional genetic algorithm are compared by the simulation results. Besides, the advantages of the improved ant colony algorithm are also analyzed. The permutation flow shop scheduling problem can be well solved by this improved ant colony algorithm.


Completion Time Work Piece Flow Shop Schedule Problem Total Weighted Completion Time Noise Method 
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  1. 1.
    Wang L (2003) Shop scheduling with genetic algorithms. Tsinghua University Press, BeijingGoogle Scholar
  2. 2.
    Garey EL, Johnson DS, Sethi R (1976) The complexity of flow-shop and job-shop scheduling. Math Oper Res 1(1):117–129MathSciNetMATHCrossRefGoogle Scholar
  3. 3.
    Zhu YJ (2007) Adaptive ant colony algorithm on the flow shop scheduling problem. Lianyungang Tech Coll 20(4):24–26Google Scholar
  4. 4.
    Liu YF, Liu SY (2008) Permutation flow shop scheduling ant colony optimization algorithm. Comput Appl 28(2):302–304Google Scholar
  5. 5.
    Zhuang XC, Lu YH, Li CX (2000) Shop scheduling based on genetic algorithm. Comput Eng 32(1):193–194Google Scholar
  6. 6.

Copyright information

© Springer Science+Business Media New York 2014

Authors and Affiliations

  1. 1.Department of Computer and Information EngineeringHeilongjiang Institute of Science and TechnologyHarbinChina

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