Abstract
Adaptation of Memetic Algorithm with Population Management for the Improvement of the Performances of Flexible Manufacturing Systems
Highlights
When traditional methods fail, it is natural to look towards some approximate resolution methods
A number of experiments are carried out which outlines the effectiveness of both the algorithms described above. The purpose of these experiments is to compare the performance of algorithm memetic with population management approach adapted to the genetic algorithm approach adapted by [2] for solving the same alternative routings selection problem
In this paper we have presented a memetic algorithm with population management approach for solving an alternative routings selection problem in an NP-hard combinatorial problem
Summary
It is natural to look towards some approximate resolution methods. Memetic algorithm with population management is a Metaheuristic that has been conceived in the last years, and proved its power in the resolution of the difficult optimization problems. The evolving manufacturing environment is characterized by a drive toward increasing flexibility. Such as the flexible manufacturing systems (FMS) which provide various advantages like the increase of resources utilization, increase of the productivity, the reduction of work in process ...etc. The Open Automation and Control Systems Journal, 2017, Volume 9 3 of a group of processing work stations, each machine, equipped with a tool magazine, can perform a variety of operations, Interconnected by an integrated transportation system [1]. To take full advantage of the FMS for production, a good scheduling system is needed. A desirable scheduling method must include two characteristics easy formulation of the problem and quick identification of semi optimal solutions [3]
Sign-in/Register to view highlights & summary 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.
