蚁群算法是一种新型的模拟进化算法，为求解复杂的组合优化问题提供了一种新的思路。
Ant colony system is a novel simulated evolutionary algorithm, which provides a new method for complicated combinatorial optimization problems.
蚁群算法是一种新型的模拟进化算法，它通过模拟蚁群在觅食过程中寻找最短路径的方法来求解优化问题。
Ant Colony optimization (ACO) is a new-style simulating evolution algorithm. The behavior of real ant colonies foraging for food is simulated and used for solving optimization problems.
蚁群算法是一种新型的模拟进化算法，重点始于组合优化问题的求解。
Ant colony algorithm is a brand-new type of simulative evolution algorithm, which focus on its solution to conform optimized question.
针对传统的PID控制器参数多采用试验加试凑的方式由人工进行优化，提出了一种新型的基于蚁群算法的PID参数优化策略。
In light of traditional PID controller parameters optimization with manual cut-and-try method, a novel kind of PID parameters optimization strategy based on ACA (Ant Colony Algorithm) was proposed.
蚁群算法是一种新型的用于求解组合优化或函数优化问题的智能优化算法。
Ant colony algorithm is a new intelligent optimization algorithm for solving combinatorial optimization problem or function optimization problem.
蚁群算法是一种新型求解复杂优化问题的启发式算法。
Ant Colony algorithm is a novel heuristic algorithm to solve complicated optimization problems.
蚁群算法作为一种新型的优化方法，具有很强的适应性和鲁棒性。
Ant colony algorithms are robust and adaptable as novel optimization methods.
蚁群算法作为一种新型的优化方法，具有很强的适应性和鲁棒性。
Ant colony algorithms are robust and adaptable as novel optimization methods.
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