Multiprocessor task scheduling in multistage hybrid flow-shops: A parallel greedy algorithm approach. Applied Soft Computing, 10(4):1293-1300, 2010.Serifoglu, F. Sivrikaya,Ulusoy, G.Multiprocessor task schedulin
Our results show that the parallel tabu search algorithm leads to much better solutions than the greedy algorithm in many cases where the latter is not capable of profiting from the inherent application parallelism and system heterogeneity. Introduction In parallel processing, the parallel portion of ...
Conflict-based strategy combined integrated optimal conflict avoidance algorithm Article Open access 15 February 2025 Combined improved A* and greedy algorithm for path planning of multi-objective mobile robot Article Open access 02 August 2022 Global and local path planning of robots combining ACO...
Wang et al. [19] proposed an optimal scheduling algorithm for minimizing job completion time (makespan) and load variance of cloud nodes. Their approach is based on GA that applies a greedy initialization and uses a double-fitness adaptive mechanism to update the population in each iteration. Au...
And an efficient collaborative greedy task scheduling algorithm was designed to achieve the optimization objective. However, little attention has been paid to the relationship between energy consumption and system performance in a UAV-assisted multi-clouds computing system. So we concentrate on the ...
The result shows that it can reduce about 40% of the energy consumption of the non-power-aware data center and reduce 1.7% energy consumption of the greedy scheduling algorithm in data center scheduling area [18]. Lin et al. used TD-error reinforcement learning to reduce the energy ...
Azizi, S., et al.: Deadline-aware and energy-efficient IoT task scheduling in fog computing systems: a semi-greedy approach. J. Netw. Comput. Appl. 201, 103333 (2022) Article Google Scholar Coello, C.C., Lechuga, M.S.: MOPSO: a proposal for multiple objective particle swarm optimiza...
The above recursive greedy algorithm can be expressed in an iterative manner. In task scheduling, we repeat the same process again and again, so iteration of the same process is computationally efficient. In this case, we have two tasks, s is set of all the tasks, and f is the set of...
Pham et al.[114]presented a taskscheduling algorithmin the Fog-Cloud environment. The proposed algorithm performs the scheduling by specifying the priorities of tasks, and determining which node to execute tasks. The obtained results show that the proposed algorithm provides an efficient balance betwee...
have proposed a novel Multi-objective algorithm to schedule tasks on a cloud environment named MGGS (modified genetic algorithm (GA) combined with greedy strategy). The MGGS algorithm was evaluated based on total completion time, average response time, and QoS parameters. The proposed genetic ...