Using dual approximation algorithms for scheduling problems theoretical and practical results
Journal of the ACM (JACM)
Scheduling precedence graphs in systems with interprocessor communication times
SIAM Journal on Computing
Automatic determination of grain size for efficient parallel processing
Communications of the ACM - Special issue: multiprocessing
Adaptation in natural and artificial systems
Adaptation in natural and artificial systems
Scheduling In and Out Forests in the Presence of Communication Delays
IEEE Transactions on Parallel and Distributed Systems
Practical genetic algorithms
Genetic Scheduling for Parallel Processor Systems: Comparative Studies and Performance Issues
IEEE Transactions on Parallel and Distributed Systems
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
A Genetic Algorithm for Multiprocessor Scheduling
IEEE Transactions on Parallel and Distributed Systems
An analysis of the behavior of a class of genetic adaptive systems.
An analysis of the behavior of a class of genetic adaptive systems.
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In the multiprocessor system, scheduling is a major issue in their operation, which is also an important problem in other area such as manufacturing, process control, economics, operation research and, etc. An efficient scheduling that minimizes the entire run time and also average of response time is vital for achieving a high performance. Solving this problem is very hard and many attempts have been made to solve the prolem, using classical algorithms and intelligent methods. In this paper, an intelligent method has been proposed based on genetic algorithm that has better performance than classical algorithms. The optimal scheduling was presented by the best chromosome in last generation.