This work studies the problem of scheduling independent tasks in heterogeneous computing grid systems. A new bi-objective formulation of the scheduling problem is introduced, which aims at minimising the makespan and weighted response ratio objectives. A novel parallel micro evolutionary algorithm is developed in order to efficiently solve the problem. By using a domain decomposition approach, the proposed method allows to efficiently deal with the multiobjective optimisation version of the scheduling problem. The new decomposition-based parallel micro evolutionary algorithm is implemented over MALLBA, a general-purpose library for combinatorial optimisation. The experimental analysis performed on both well-known and new large problem instances that model medium-sized grid environments demonstrate that the new parallel micro evolutionary algorithm achieves a high problem-solving efficacy and shows very good scalability behaviour when facing high-dimensional instances.
['Sergio Nesmachnow', 'Santiago Iturriaga']
Multiobjective grid scheduling using a domain decomposition based parallel micro evolutionary algorithm