Abstract
To solve the job-shop scheduling problem more effectively, a method based on a novel scheduling algorithm named immune genetic algorithm (IGA) was proposed. In this study, the framework of IGA was presented via combining the immune theory and the genetic algorithm. The encoding scheme based on processes and the adaptive probabilities of crossover and mutation were adopted, while a modified precedence operation crossover was also proposed to improve the performance of the crossover operator. On the other hand, the “shortest processing time” principle was selected to be the vaccine of IGA and the design method of the immune operator was given at the same time. Finally, the performance of IGA for solving JSP was validated by applying the IGA to Muth and Thompson’s benchmark problems.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callMore From: The International Journal of Advanced Manufacturing Technology
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
