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Information Technology Journal
  Year: 2007 | Volume: 6 | Issue: 6 | Page No.: 929-933
DOI: 10.3923/itj.2007.929.933
 
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Improved Artificial Immune Algorithm and its application on the Permutation Flow Shop Sequencing Problems

Haichang Gao and Xiyang Liu

Abstract:
Flow shop sequencing is one of the most well-known production scheduling problems and a typical NP-hard combinatorial optimization problem with strong engineering background. To efficiently deal with permutation flow shop sequencing problems, a novel algorithm, Artificial Immune Algorithm (AIA) is proposed which is inspired by the immune system of human to simulate the process of the interaction between antigens, antibodies and memory cells. The algorithm is tested on some benchmarks. Experimental results show AIA is quite flexible with satisfactory results and require fewer running time than Genetic Algorithms and Simulated Annealing.
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How to cite this article:

Haichang Gao and Xiyang Liu, 2007. Improved Artificial Immune Algorithm and its application on the Permutation Flow Shop Sequencing Problems. Information Technology Journal, 6: 929-933.

DOI: 10.3923/itj.2007.929.933

URL: https://scialert.net/abstract/?doi=itj.2007.929.933

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