A Memetic Algorithm with Particle Swarm Optimization and Differential Evolution Algorithm to Rescheduling Problem in Multi-Agent System
Dynamic rescheduling model and its solution method are of significant importance for the dynamic scheduling problem in manufacturing system. However, few attempts have been done on the universal communication and negotiation mechanism for the dynamic rescheduling problem and corresponding solution approach. A dynamic rescheduling model, which is based on Multi-Agent System (MAS), was proposed. A memetic algorithm with PSO (particle swarm optimization) and DE (differential evolution) was presented as the solution method to the rescheduling model. Furthermore, the simulation results in dynamic scheduling accompanying with its perturbation show that the proposed model and the algorithm are effective to the dynamic scheduling problem in manufacturing system.
No Reference information available - sign in for access.
No Citation information available - sign in for access.
No Supplementary Data.
No Article Media
Document Type: Research Article
Publication date: March 1, 2012
More about this publication?
- ADVANCED SCIENCE LETTERS is an international peer-reviewed journal with a very wide-ranging coverage, consolidates research activities in all areas of (1) Physical Sciences, (2) Biological Sciences, (3) Mathematical Sciences, (4) Engineering, (5) Computer and Information Sciences, and (6) Geosciences to publish original short communications, full research papers and timely brief (mini) reviews with authors photo and biography encompassing the basic and applied research and current developments in educational aspects of these scientific areas.
- Editorial Board
- Information for Authors
- Subscribe to this Title
- Ingenta Connect is not responsible for the content or availability of external websites