蚁群算法在处理大规模优化问题时效率很低。

Two improvements on Ant Colony Optimization(ACO) algorithm is presented in this paper.

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本文在利用优化性质的基础上，提出了一种适于大规模优化调度问题的多项式时间算法。

Basing on the optimal properties, this paper proposes a polynomial time algorithm which is suitable to solve the large scale scheduling problem.

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因此，包括涉及大规模决策变量及大规模优化目标在内的优化问题对现有自然启发式算法提出了很高的挑战。

Hence, large optimization problems that involve either a large number of decision variables or many objectives pose great challenges to the current research in nature-inspired optimization.

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