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
Proceedings of the 1992 ACM/IEEE conference on Supercomputing
Task scheduling in parallel and distributed systems
Task scheduling in parallel and distributed systems
Applied Numerical Mathematics - Special issue: a festschrift to honor Professor Robert Vichnevetsky on his 65th birthday
Multiprocessor scheduling in a genetic paradigm
Parallel Computing
Computers and Operations Research
On Exploiting Task Duplication in Parallel Program Scheduling
IEEE Transactions on Parallel and Distributed Systems
Genetic Scheduling for Parallel Processor Systems: Comparative Studies and Performance Issues
IEEE Transactions on Parallel and Distributed Systems
Scheduling Multiprocessor Tasks with Genetic Algorithms
IEEE Transactions on Parallel and Distributed Systems
Static scheduling algorithms for allocating directed task graphs to multiprocessors
ACM Computing Surveys (CSUR)
Parallel Computer Architecture: A Hardware/Software Approach
Parallel Computer Architecture: A Hardware/Software Approach
Performance-Effective and Low-Complexity Task Scheduling for Heterogeneous Computing
IEEE Transactions on Parallel and Distributed Systems
Hypertool: A Programming Aid for Message-Passing Systems
IEEE Transactions on Parallel and Distributed Systems
A Genetic Algorithm for Multiprocessor Scheduling
IEEE Transactions on Parallel and Distributed Systems
An Incremental Genetic Algorithm Approach to Multiprocessor Scheduling
IEEE Transactions on Parallel and Distributed Systems
Parallel Metaheuristics: A New Class of Algorithms
Parallel Metaheuristics: A New Class of Algorithms
Genetic algorithm for the personnel assignment problem with multiple objectives
Information Sciences: an International Journal
Statistical Comparisons of Classifiers over Multiple Data Sets
The Journal of Machine Learning Research
Optimizing task schedules using an artificial immune system approach
Proceedings of the 10th annual conference on Genetic and evolutionary computation
A multi-modal immune algorithm for the job-shop scheduling problem
Information Sciences: an International Journal
Expert Systems with Applications: An International Journal
A hybrid evolutionary approach for heterogeneous multiprocessor scheduling
Soft Computing - A Fusion of Foundations, Methodologies and Applications - Special Issue on Emerging Trends in Soft Computing - Memetic Algorithms; Guest Editors: Yew-Soon Ong, Meng-Hiot Lim, Ferrante Neri, Hisao Ishibuchi
A robust scheduling method based on a multi-objective immune algorithm
Information Sciences: an International Journal
Genetic algorithms for task scheduling problem
Journal of Parallel and Distributed Computing
A bipartite genetic algorithm for multi-processor task scheduling
International Journal of Parallel Programming
NP-complete scheduling problems
Journal of Computer and System Sciences
Information Sciences: an International Journal
A tutorial for competent memetic algorithms: model, taxonomy, and design issues
IEEE Transactions on Evolutionary Computation
Information Sciences: an International Journal
A parallel micro evolutionary algorithm for heterogeneous computing and grid scheduling
Applied Soft Computing
Information Sciences: an International Journal
A novel algorithm for dynamic task scheduling
Future Generation Computer Systems
Information Sciences: an International Journal
Variable neighborhood search for robust optimization and applications to aerodynamics
LSSC'11 Proceedings of the 8th international conference on Large-Scale Scientific Computing
Information Sciences: an International Journal
Information Sciences: an International Journal
A hybrid heuristic-genetic algorithm for task scheduling in heterogeneous multi-core system
ICA3PP'12 Proceedings of the 12th international conference on Algorithms and Architectures for Parallel Processing - Volume Part I
Combinatorial complexity problem reduction by the use of artificial vaccines
Expert Systems with Applications: An International Journal
Information Sciences: an International Journal
Computers and Operations Research
Proceedings of the 15th annual conference on Genetic and evolutionary computation
Computational Optimization and Applications
A discrete gravitational search algorithm for solving combinatorial optimization problems
Information Sciences: an International Journal
Hi-index | 0.07 |
Effective task scheduling, which is essential for achieving high performance in a heterogeneous multiprocessor system, remains a challenging problem despite extensive studies. In this article, a heuristic-based hybrid genetic-variable neighborhood search algorithm is proposed for the minimization of makespan in the heterogeneous multiprocessor scheduling problem. The proposed algorithm distinguishes itself from many existing genetic algorithm (GA) approaches in three aspects. First, it incorporates GA with the variable neighborhood search (VNS) algorithm, a local search metaheuristic, to exploit the intrinsic structure of the solutions for guiding the exploration process of GA. Second, two novel neighborhood structures are proposed, in which problem-specific knowledge concerned with load balancing and communication reduction is utilized respectively, to improve both the search quality and efficiency of VNS. Third, the proposed algorithm restricts the use of GA to evolve the task-processor mapping solutions, while taking advantage of an upward-ranking heuristic mostly used by traditional list scheduling approaches to determine the task sequence assignment in each processor. Empirical results on benchmark task graphs of several well-known parallel applications, which have been validated by the use of non-parametric statistical tests, show that the proposed algorithm significantly outperforms several related algorithms in terms of the schedule quality. Further experiments are carried out to reveal that the proposed algorithm is able to maintain high performance within a wide range of parameter settings.