关键词: 多目标猫群算法, 线性混合比率, 多目标集成效用函数, 智能调度

Abstract:

Considering the multi-objective conflict problem for job scheduling in cloud computing environment,this paper proposes an optimized multi-objective cat swarm algorithm (MO-CSO) based on cat behavior using the linear mixture ratio selection method to improve the global search and local optimization ability.The algorithm combines the makespan and total cost to propose an adjustable multi-objective integrated utility function,which implements the intelligent dispatching of resources and task.The experimental results show that the optimized MO-CSO not only has high quality,but also are superior in solving speed and scheduling costs to the multi-objective genetic algorithm (MO-GA) and the multi-objective particle swarm optimization (MO-PSO) algorithm.

Key words: multi objective cat swarm algorithm;linear mixing ratio;a multi objective integrated utility function;intelligent scheduling