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)

Abstract

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.

Keywords

Line Production Volatility 

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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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