Evolutionary Algorithm for Solving Constrained Multi-Objective Grid Tasks Scheduling Problem

For solving tasks scheduling problem under heterogeneous grid environment, a new constrained multiobjective grid tasks scheduling model is proposed. Firstly, a security benefit function is constructed under considering the inherent security of grid nodes; secondly, a node´s reputation dynamic evaluation model is constructed based on the behavior of grid nodes. In order to solve the model, the multi-objective model is transformed into a single-objective model in terms of the subjection degree function; meanwhile, a new crossover operator and an even mutation operator is proposed. Based on all of these, a new evolutionary algorithm is presented. Finally, simulation results show that the proposed algorithm is better than the compared ones in terms of the length of the task scheduling, security efficiency value and reliability.