ant colony optimization信息详情
蚁群优化算法
colony───n.殖民地;移民队;种群;动物栖息地
ant───n.蚂蚁;n.(Ant)人名;(土、芬)安特
sequel colony───续集殖民地
constrained optimization───条件最佳化;[分化][数]约束优化;[分化][数]有约束优化
delivery optimization───交付优化
calculus optimization───微积分优化
colony collapse───蜂群崩溃
optimization terminated───优化终止
leper colony───麻风病人隔离区
An ant colony optimization based algorithm for permutation flow shop scheduling was proposed.───了一种求解置换流水车间调度的蚁群优化算法。
optimal unit commitment is solved via the Ant Colony Optimization algorithm in this paper.───优化算法——蚁群优化算法来求解机组最优启停问题。
Ant colony optimization for mixed-model assembly line balancing problem (MMALBP) is studied.───研究了混合型装配线平衡问题的智能蚁群优化算法。
The ant colony optimization algorithm has found slow convergence and easy to stagnation.───发现基本蚁群优化算法存在慢收敛且易停滞等问题。
Compared with gradient-type methods, the ant colony optimization is able to converge to global minima for estimating model parameters.───与传统的基于梯度的优化方法相比较,对于参数识别反问题蚁群算法能够收敛到全局最优解。
Ant colony optimization (ACO) has high optimizing efficiency, but can only be applied to combinational optimization problems.───经典蚁群优化(ACO)算法搜优效率高,但只适用于求解组合优化等离散问题。
Test results show that the ant colony optimization can be used in the accurate classification fault location in the nuclear power plants.───利用文献中的数据对该系统进行了测试,结果表明利用蚁群算法可以准确地对核能动力系统进行分级故障定位。
This paper makes primary researches to the distribution center location on the basis of the prevalent ant colony optimization algorithm.───本文在解决配送中心选址问题中着重使用现在流行的蚁群优化算法对给出的配送中心选址模型进行求解。
The key point of this algorithm is to integrate NEH heuristics with ant colony optimization.───该算法的要点是结合了NEH启发式算法和蚁群优化方法。
An improved ant colony optimization ( ACO ) algorithm is utilized in cell scheduling of flexibleforinstrumentand time.
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.
Finally, the author combined the impedance function which is built up based on GM (1,1) model with the ant colony optimization, and got the flow chart.
The system combined the Ant Colony Optimization (ACO) algorithm and the dispatching priority heuristic algorithm to solve the scheduling problems existing in mold parts with work piece restrictions.
Then, the ant colony optimization algorithm has been used to solve optimal scheduling problems.
Ant Colony Optimization (ACO), which is introduced in this paper because of the ability of resisting combination explosion to NP-hard problem, now is used to solve the problem of DNO.
An ant colony optimization based algorithm for permutation flow shop scheduling was proposed.
Ant Colony Optimization Algorithms ( ACOAs ) were appropriate for this optimization problem.
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