New computer methods for global optimization
New computer methods for global optimization
Scheduling precedence graphs in systems with interprocessor communication times
SIAM Journal on Computing
Adaptation in natural and artificial systems
Adaptation in natural and artificial systems
Task scheduling in parallel and distributed systems
Task scheduling in parallel and distributed systems
Genetic algorithms + data structures = evolution programs (2nd, extended ed.)
Genetic algorithms + data structures = evolution programs (2nd, extended ed.)
Computer
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Parallel Processing for Real-Time Simulation: A Case Study
IEEE Parallel & Distributed Technology: Systems & Technology
A Generalized Scheme for Mapping Parallel Algorithms
IEEE Transactions on Parallel and Distributed Systems
A Genetic Algorithm for Multiprocessor Scheduling
IEEE Transactions on Parallel and Distributed Systems
DSC: Scheduling Parallel Tasks on an Unbounded Number of Processors
IEEE Transactions on Parallel and Distributed Systems
Static task scheduling and grain packing in parallel processing systems
Static task scheduling and grain packing in parallel processing systems
A parallel computing engine for a class of time critical processes
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Observations on Using Genetic Algorithms for Dynamic Load-Balancing
IEEE Transactions on Parallel and Distributed Systems
Sequential and Parallel Cellular Automata-Based Scheduling Algorithms
IEEE Transactions on Parallel and Distributed Systems
Performance of Evolutionary Approaches for Parallel Task Scheduling under Different Representations
Proceedings of the Applications of Evolutionary Computing on EvoWorkshops 2002: EvoCOP, EvoIASP, EvoSTIM/EvoPLAN
Multiprocessor Clustering for Embedded Systems
Euro-Par '01 Proceedings of the 7th International Euro-Par Conference Manchester on Parallel Processing
Journal of Parallel and Distributed Computing - Special issue on wireless and mobile ad hoc networking and computing
An Incremental Genetic Algorithm Approach to Multiprocessor Scheduling
IEEE Transactions on Parallel and Distributed Systems
Dynamic Task Scheduling using Genetic Algorithms for Heterogeneous Distributed Computing
IPDPS '05 Proceedings of the 19th IEEE International Parallel and Distributed Processing Symposium (IPDPS'05) - Workshop 6 - Volume 07
Framework for Task Scheduling in Heterogeneous Distributed Computing Using Genetic Algorithms
Artificial Intelligence Review
On multiprocessor task scheduling using efficient state space search approaches
Journal of Parallel and Distributed Computing
Efficient Techniques for Clustering and Scheduling onto Embedded Multiprocessors
IEEE Transactions on Parallel and Distributed Systems
Efficient Compile-Time Task scheduling for Heterogeneous Distributed Computing Systems
ICPADS '06 Proceedings of the 12th International Conference on Parallel and Distributed Systems - Volume 1
Expert Systems with Applications: An International Journal
A performance study of multiprocessor task scheduling algorithms
The Journal of Supercomputing
Journal of Parallel and Distributed Computing
Scientific Programming - Scientific Workflows
Evolutionary minimization of the Rand index for speaker clustering
Computer Speech and Language
Minimizing Energy Consumption for Precedence-Constrained Applications Using Dynamic Voltage Scaling
CCGRID '09 Proceedings of the 2009 9th IEEE/ACM International Symposium on Cluster Computing and the Grid
Task scheduling in distributed environment using genetic algorithm
AIC'09 Proceedings of the 9th WSEAS international conference on Applied informatics and communications
A memetic algorithm for reliability-based dynamic scheduling in heterogeneous computing environments
PDCS '07 Proceedings of the 19th IASTED International Conference on Parallel and Distributed Computing and Systems
Contributions to the multiprocessor scheduling problem
CI '07 Proceedings of the Third IASTED International Conference on Computational Intelligence
Scheduling task graphs optimally with A*
The Journal of Supercomputing
Journal of Parallel and Distributed Computing
Robust task scheduling for volunteer computing systems
The Journal of Supercomputing
A heuristic-based hybrid genetic algorithm for heterogeneous multiprocessor scheduling
Proceedings of the 12th annual conference on Genetic and evolutionary computation
Optimized parallelization heuristic for task scheduling
CI'10 Proceedings of the 4th WSEAS international conference on Computational intelligence
Information Sciences: an International Journal
Genetic algorithm for satellite customer assignment
ICONIP'06 Proceedings of the 13th international conference on Neural information processing - Volume Part III
A hybrid heuristic-genetic algorithm for task scheduling in heterogeneous processor networks
Journal of Parallel and Distributed Computing
A parallel bi-objective hybrid metaheuristic for energy-aware scheduling for cloud computing systems
Journal of Parallel and Distributed Computing
ICNC'05 Proceedings of the First international conference on Advances in Natural Computation - Volume Part II
Optimal linear programming solutions for multiprocessor scheduling with communication delays
ICA3PP'12 Proceedings of the 12th international conference on Algorithms and Architectures for Parallel Processing - Volume Part I
Reducing the solution space of optimal task scheduling
Computers and Operations Research
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Task scheduling is essential for the proper functioning of parallel processor systems. Scheduling of tasks onto networks of parallel processors is an interesting problem that is well-defined and documented in the literature. However, most of the available techniques are based on heuristics that solve certain instances of the scheduling problem very efficiently and in reasonable amounts of time. This paper investigates an alternative paradigm, based on genetic algorithms, to efficiently solve the scheduling problem without the need to apply any restricted assumptions that are problem-specific, such is the case when using heuristics. Genetic algorithms are powerful search techniques based on the principles of evolution and natural selection. The performance of the genetic approach will be compared to the well-known list scheduling heuristics. The conditions under which a genetic algorithm performs best will also be highlighted. This will be accompanied by a number of examples and case studies.