  Grid computing is the recently growing area of computing that share data,
storage, computing across geographically dispersed area. This paper proposes a
novel fuzzy approach using Differential Evolution (DE) for scheduling jobs on
computational grids. The fuzzy based DE generates an optimal plan to complete
the jobs within a minimum period of time. We evaluate the performance of the
proposed fuzzy based DE algorithm with Genetic Algorithm (GA), Simulated
Annealing (SA), Differential Evolution and fuzzy PSO. Experimental results have
shown that the new algorithm produces more optimal solutions for the job
scheduling problems compared to other algorithms.
