1) local optimization searching strategy
局部最优搜索策略
1.
To overcome these deficiencies resulting in the precocity and stagnation,the parameters of the city selective strategy and the local optimization searching strategy are adopted.
为了克服标准蚁群算法容易陷入局部最优化从而导致算法过早停滞的缺陷,论文引入了城市选择策略的变参数和局部最优搜索策略,同时对信息激素的更新方式提出了相应的改进策略,并应用于对TSP问题的仿真实验。
2) Local search strategy
局部搜索策略
1.
TU Li.Differential evolution algorithm with local search strategy
具有局部搜索策略的差分进化算法
2.
In this paper,we established the mathematical model of assignment problem as well as described assignment problem as a TSP diagram,then solved it by using ant colony algorithm with a local search strategy.
本文将指派问题表述为TSP图,使用具有局部搜索策略的蚁群算法加以解决。
3) control tragedy for searching the best result in different layers
分层全局最优搜索控制策略
4) chaotic-local-search strategy
混沌局部搜索策略
1.
Differential evolution algorithm with chaotic-local-search strategy for global optimization
具有混沌局部搜索策略的差分进化全局优化算法
5) circling strategy of local extreme values
局部最优徘徊策略
1.
The improvements of NGA are as following:the discriminating standard L for distances among individuals set as dynamic function to keep the diversity of colonies;the elitist strategy is adopted to ensure the convergence of the algorithm;the circling strategy of local extreme values is used as auxiliary termination principle to avoid falling into local optima.
算法主要做了以下改进:设置个体之间的距离判别标准L为动态函数,保持了群体的多样性;采用最优保存策略保证算法的收敛性;采用局部最优徘徊策略作为辅助终止原则,避免陷入局部最优情况。
6) optimal policy search
优化策略搜索
1.
Based on the policy search algorithm in partially observable Markov decision process(POMDP),an optimal policy search algorithm is proposed.
研究结果揭示了匹配行为与优化策略搜索算法之间的关系,表明满足匹配律的决策行为是一类达到次优的决策行为。
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