Introduction to algorithms
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
GSA: scheduling and allocation using genetic algorithm
EURO-DAC '94 Proceedings of the conference on European design automation
A parallel genetic algorithm for the set partitioning problem
A parallel genetic algorithm for the set partitioning problem
IEEE Transactions on Parallel and Distributed Systems
Parallel computation: models and methods
Parallel computation: models and methods
Benchmarking and comparison of the task graph scheduling algorithms
Journal of Parallel and Distributed Computing
Static scheduling algorithms for allocating directed task graphs to multiprocessors
ACM Computing Surveys (CSUR)
Low-Cost Task Scheduling for Distributed-Memory Machines
IEEE Transactions on Parallel and Distributed Systems
Hypertool: A Programming Aid for Message-Passing Systems
IEEE Transactions on Parallel and Distributed Systems
IEEE Transactions on Parallel and Distributed Systems
A Genetic Algorithm for Multiprocessor Scheduling
IEEE Transactions on Parallel and Distributed Systems
A Mathematical Analysis of Tournament Selection
Proceedings of the 6th International Conference on Genetic Algorithms
A Parallel Genetic Algorithm for Task Mapping on Parallel Machines
Proceedings of the 11 IPPS/SPDP'99 Workshops Held in Conjunction with the 13th International Parallel Processing Symposium and 10th Symposium on Parallel and Distributed Processing
High-performance algorithms of compile-time scheduling of parallel processors
High-performance algorithms of compile-time scheduling of parallel processors
Parallel Programming: Techniques and Applications Using Networked Workstations and Parallel Computers (2nd Edition)
An Incremental Genetic Algorithm Approach to Multiprocessor Scheduling
IEEE Transactions on Parallel and Distributed Systems
A New Approach to Scheduling Parallel Programs Using Task Duplication
ICPP '94 Proceedings of the 1994 International Conference on Parallel Processing - Volume 02
Evolutionary computation: comments on the history and current state
IEEE Transactions on Evolutionary Computation
Information Sciences: an International Journal
Journal of Parallel and Distributed Computing
Recursive structure element decomposition using migration fitness scaling genetic algorithm
ICSI'11 Proceedings of the Second international conference on Advances in swarm intelligence - Volume Part I
A novel algorithm for dynamic task scheduling
Future Generation Computer Systems
Maximum-throughput mapping of SDFGs on multi-core SoC platforms
Journal of Parallel and Distributed Computing
The Journal of Supercomputing
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The scheduling and mapping of the precedence-constrained task graph to processors is considered to be the most crucial NP-complete problem in parallel and distributed computing systems. Several genetic algorithms have been developed to solve this problem. A common feature in most of them has been the use of chromosomal representation for a schedule. However, these algorithms are monolithic, as they attempt to scan the entire solution space without considering how to reduce the complexity of the optimization process. In this paper, two genetic algorithms have been developed and implemented. Our developed algorithms are genetic algorithms with some heuristic principles that have been added to improve the performance. According to the first developed genetic algorithm, two fitness functions have been applied one after the other. The first fitness function is concerned with minimizing the total execution time (schedule length), and the second one is concerned with the load balance satisfaction. The second developed genetic algorithm is based on a task duplication technique to overcome the communication overhead. Our proposed algorithms have been implemented and evaluated using benchmarks. According to the evolved results, it has been found that our algorithms always outperform the traditional algorithms.