A study of permutation crossover operators on the traveling salesman problem
Proceedings of the Second International Conference on Genetic Algorithms on Genetic algorithms and their application
Benchmarking and comparison of the task graph scheduling algorithms
Journal of Parallel and Distributed Computing
Observations on Using Genetic Algorithms for Dynamic Load-Balancing
IEEE Transactions on Parallel and Distributed Systems
Introduction to Algorithms
Link contention-constrained scheduling and mapping of tasks
Cluster Computing
SSST '96 Proceedings of the 28th Southeastern Symposium on System Theory (SSST '96)
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
Toward a Realistic Task Scheduling Model
IEEE Transactions on Parallel and Distributed Systems
Task Scheduling for Parallel Systems (Wiley Series on Parallel and Distributed Computing)
Task Scheduling for Parallel Systems (Wiley Series on Parallel and Distributed Computing)
Computers and Operations Research
Task scheduling algorithm using minimized duplications in homogeneous systems
Journal of Parallel and Distributed Computing
Expert Systems with Applications: An International Journal
A Survey and Future Trend of Study on Multi-Objective Scheduling
ICNC '08 Proceedings of the 2008 Fourth International Conference on Natural Computation - Volume 06
Real-time task scheduling by multiobjective genetic algorithm
Journal of Systems and Software
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Task scheduling is an essential aspect of parallel processing system This problem assumes fully connected processors and ignores contention on the communication links However, as arbitrary processor network (APN), communication contention has a strong influence on the execution time of a parallel application In this paper, we propose multi-objective genetic algorithm to solve task scheduling problem with time constraints in unstructured heterogeneous processors to find the scheduling with minimum makespan and total tardiness To optimize objectives, we use Pareto front based technique, vector based method In this problem, just like tasks, we schedule messages on suitable links during the minimization of the makespan and total tardiness To find a path for transferring a message between processors we use classic routing algorithm We compare our method with BSA method that is a well known algorithm Experimental results show our method is better than BSA and yield better makespan and total tardiness.