Paper Info
Title
Multi-agent System for Dynamic Manufacturing System Optimization
Abstract
This paper deals with the application of multi-agent system concept for optimization of dynamic uncertain process. These problems are known to have a computationally demanding objective function, which could turn to be infeasible when large problems are considered. Therefore, fast approximations to the objective function are required. This paper employs bundle of intelligent systems algorithms tied together in a multi-agent system. In order to demonstrate the system, a metal reheat furnace scheduling problem is adopted for highly demanded optimization problem. The proposed multi-agent approach has been evaluated for different settings of the reheat furnace scheduling problem. Particle Swarm Optimization, Genetic Algorithm with different classic and advanced versions: GA with chromosome differentiation, Age GA, and Sexual GA, and finally a Mimetic GA, which is based on combining the GA as a global optimizer and the PSO as a local optimizer. Experimentation has been performed to validate the multi-agent system on the reheat furnace scheduling problem.
Year
DOI
Venue
2008
10.1007/978-3-540-69389-5_71
ICCS (3)
Keywords
Field
DocType
mimetic ga,dynamic manufacturing system optimization,reheat furnace scheduling problem,multi-agent system,optimization problem,age ga,objective function,intelligent system,multi-agent system concept,large problem,sexual ga,difference set,genetic algorithm,multi agent system,global optimization,scheduling,scheduling problem
Particle swarm optimization,Mathematical optimization,Job shop scheduling,Intelligent decision support system,Scheduling (computing),Computer science,Multi-agent system,Optimization problem,Genetic algorithm,Bundle
Conference
Volume
ISSN
Citations 
5103
0302-9743
1
PageRank 
References 
Authors
0.43
4
2
Name
Order
Citations
PageRank
Tawfeeq Al-Kanhal110.43
Maysam Abbod2387.15