Multiprocessor scheduling in a genetic paradigm
Parallel Computing
LEneS: task scheduling for low-energy systems using variable supply voltage processors
Proceedings of the 2001 Asia and South Pacific Design Automation Conference
Task scheduling and voltage selection for energy minimization
Proceedings of the 39th annual Design Automation Conference
Energy-Efficient Mapping and Scheduling for DVS Enabled Distributed Embedded Systems
Proceedings of the conference on Design, automation and test in Europe
Fast and efficient voltage scheduling by evolutionary slack distribution
Proceedings of the 2004 Asia and South Pacific Design Automation Conference
GAARP: A Power-Aware GALS Architecture for Real-Time Algorithm-Specific Tasks
IEEE Transactions on Computers
ASP-DAC '03 Proceedings of the 2003 Asia and South Pacific Design Automation Conference
ACM Transactions on Design Automation of Electronic Systems (TODAES)
IEEE Transactions on Parallel and Distributed Systems
Scheduling: Theory, Algorithms, and Systems
Scheduling: Theory, Algorithms, and Systems
Power-aware scheduling for makespan and flow
Journal of Scheduling
Dynamic slack allocation algorithms for energy minimization on parallel machines
Journal of Parallel and Distributed Computing
Journal of Intelligent Manufacturing
Systematic decision process for intelligent decision making
Journal of Intelligent Manufacturing
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
Power-Efficient Scheduling for Heterogeneous Distributed Real-Time Embedded Systems
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
Metaheuristics and exact methods to solve a multiobjective parallel machines scheduling problem
Journal of Intelligent Manufacturing
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In this paper, a new heuristic called bat intelligence (BI) is introduced for solving energy aware multiprocessor scheduling problems. Bat intelligence is a novel optimization method that models prey hunting behaviors of bats. Bat intelligence and genetic algorithm (GA) are used to solve single-objective multiprocessor scheduling problem using, makespan, tardiness, and energy consumption as objective functions. Bat intelligence shows considerable improvement in terms of solution quality when compared with GA. Different combinations of these objectives are used to solve bi-objective multiprocessor scheduling problems, (makespan vs. energy, and also tardiness vs. energy). Tri-objective multiprocessor scheduling problem is also presented at the end. To generate desirable efficient alternatives, a Normalized Weighted Additive Utility Function is used. Simulation shows that BI identifies a set of efficient solutions that correspond to the assigned weights. The computational simulation also shows conflicting relationships between makespan and energy, and also between tardiness and energy.