Abstract
Aiming at the problem that the AGV energy consumption is not considered in the multi-task mode, a multi-task model is established which takes the total energy consumption of AGV and the total time of tasks out of warehouse as the goal, and the task group reconstruction is realized based on the batch-combination strategy. Then, this paper improves the NSGA-II algorithm to solve the model from the following three aspects: population screening mechanism, pheromone-based crossover, and double mutation operate. The experimental simulation results show that the improved NSGA-II algorithm improves the quality of the solutions, and meanwhile improves the stability of the algorithm compared with theoriginal NSGA-II algorithm.
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.
