Abstract
This paper mainly focused on 0/1 knapsack problems based on the genetic algorithm (GA). According to characteristics of the individual independence in GA, a parallel segmentation method was presented using the OpenCL technology in resolving the 0/1 knapsack problems. Moreover, the local memory was partially optimized in the statistical operation of GA. Experiment results in comparing serial and parallel algorithm implementations showed that the parallel algorithm implementation was operative and the execution time of the parallel algorithm implementation increased linearly according to the increment of problem scale. By comparing the execution time of implementations on CPU and GPU under various individuals and iterations conditions, the effects on CPU and GPU of this method were also analyzed.
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 callDisclaimer: 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.
