APPLYING THE CLONAL SELECTION PRINCIPLE TO SOLVING FLEXIBLE JOB-SHOP SCHEDULING PROBLEM

Authors

  • Ahmad Shahrizal Muhamad Universiti Teknologi Malaysia (UTM), Johor
  • Safaai Deris Universiti Teknologi Malaysia, Johor

Keywords:

scheduling, artificial intelligence, flexible job-shop scheduling, robustness, artificial immune system, evolutionary computation

Abstract

This work deals with the problems of flexible job-shop scheduling and proposes ways to find the most optimal and robust solutions. Finding such solutions is of the utmost important for real- world applications, as scheduling operates in a dynamic environment. Several methods have been used to solve job-shop scheduling problems and the method proposed here is artificial intelligence by using the clonal selection principle algorithm. The advantage of this algorithm is that it is structured in such a way as to imitate the natural immune system. The results produced by this method compare well with the results of previous research

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Published

2016-09-11

How to Cite

Ahmad Shahrizal Muhamad, & Safaai Deris. (2016). APPLYING THE CLONAL SELECTION PRINCIPLE TO SOLVING FLEXIBLE JOB-SHOP SCHEDULING PROBLEM. JOURNAL INFORMATION AND TECHNOLOGY MANAGEMENT (JISTM), 1(1), 18–36. Retrieved from https://gaexcellence.com/jistm/article/view/878

Issue

Vol. 1 No. 1 (2016): Volume_ 1 Issues_ 1 [September, 2016]

Section

Articles