In this article a mathematical model with twin objectives is presented. The objectives are consideredas: Minimization of the maximum tardiness of tasks completion time and the total early taskspenalties. Since tasks timing is a tardy and indefinite factor in cloud computing; therefore problemsolving model is used as the combined Meta-heuristic innovative algorithm of multi objective swarmof particles based Parto archive has been used. The suggested algorithm with genetic operatorsas well as the directed and repeated counterpart structures in the format of multi operators aretaken to assess the algorithm application. The results will be sorted based on quality, distraction,integrated, the number of non-defeated solutions and the gap from the ideal one is compared withthe evolutionary algorithm results titled genetic algorithm. The final results of solved model indicatethat firstly, this algorithm is stronger than NSGA-II algorithm but is weaker in timing, norms andscales. In other words, the suggested algorithm, is more capable to discover solutions, accordingly.

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