The topographic information of a closed world is expressed as a graph. The plural mov- ingobjects which go and back in it according to a single moving strategy are supposed.The moving strategy is expressed by numerica...The topographic information of a closed world is expressed as a graph. The plural mov- ingobjects which go and back in it according to a single moving strategy are supposed.The moving strategy is expressed by numerical values as a decision table. Coding is performed with this table as chromosomes, and this is optimized by using genetic algorithm. These environments were realized on a computer, and the simulation was carried out. As the result, the learning of the method to act so that moving objects do not obstruct mutually was recognized, and it was confirmed that these methods are effective for optimizing moving strategy.展开更多
The forum on the strategy for implementing the vitalization of the northeastold industry base was held on June 13^(th), 2005 in Shengyang by the General Adminitration ofQuality supervision, Inspection and Quarantine o...The forum on the strategy for implementing the vitalization of the northeastold industry base was held on June 13^(th), 2005 in Shengyang by the General Adminitration ofQuality supervision, Inspection and Quarantine of P.R. China (AQSIQ). The leaders in charge of theState Council Office of Northeast Vitalization and the Provincial Office of Vitalization ofLiaoning, Jilin and Heilongjiang were invited to attend the forum. At the forum, Director of AQSIQLi Changjiang made active response to the issues surrounding 'how the central government policy ofvitalizing Northeast can be fulfilled' and 'how the departments of quality inspection can fulfilltheir duty and play an active role'.展开更多
针对多模态多目标优化中种群多样性难以维持和所得等价Pareto最优解数量不足问题,提出一种融合聚类和小生境搜索的多模态多目标优化算法(multimodal multi-objective optimization algorithm with clustering and niching searching,CSS...针对多模态多目标优化中种群多样性难以维持和所得等价Pareto最优解数量不足问题,提出一种融合聚类和小生境搜索的多模态多目标优化算法(multimodal multi-objective optimization algorithm with clustering and niching searching,CSSMPIO)。首先利用基于聚类的特殊拥挤距离非支配排序方法(clustering-based special crowding distance,CSCD)初始化种群;引入自适应物种形成策略生成稳定的小生境,在不同的小生境子空间并行搜索和保持等价Pareto最优解;采用特殊拥挤距离非支配排序策略实现个体选优、精英学习策略避免过早收敛。通过在14个多模态多目标函数上进行测试,并与7种新提出的多模态多目标优化算法进行对比实验以及Wilcoxon秩和检验发现,CSSMPIO的总体性能优于对比算法。最后将算法用于基于地图的测试问题,进一步证明了算法的有效性。展开更多
文摘The topographic information of a closed world is expressed as a graph. The plural mov- ingobjects which go and back in it according to a single moving strategy are supposed.The moving strategy is expressed by numerical values as a decision table. Coding is performed with this table as chromosomes, and this is optimized by using genetic algorithm. These environments were realized on a computer, and the simulation was carried out. As the result, the learning of the method to act so that moving objects do not obstruct mutually was recognized, and it was confirmed that these methods are effective for optimizing moving strategy.
文摘The forum on the strategy for implementing the vitalization of the northeastold industry base was held on June 13^(th), 2005 in Shengyang by the General Adminitration ofQuality supervision, Inspection and Quarantine of P.R. China (AQSIQ). The leaders in charge of theState Council Office of Northeast Vitalization and the Provincial Office of Vitalization ofLiaoning, Jilin and Heilongjiang were invited to attend the forum. At the forum, Director of AQSIQLi Changjiang made active response to the issues surrounding 'how the central government policy ofvitalizing Northeast can be fulfilled' and 'how the departments of quality inspection can fulfilltheir duty and play an active role'.
文摘针对多模态多目标优化中种群多样性难以维持和所得等价Pareto最优解数量不足问题,提出一种融合聚类和小生境搜索的多模态多目标优化算法(multimodal multi-objective optimization algorithm with clustering and niching searching,CSSMPIO)。首先利用基于聚类的特殊拥挤距离非支配排序方法(clustering-based special crowding distance,CSCD)初始化种群;引入自适应物种形成策略生成稳定的小生境,在不同的小生境子空间并行搜索和保持等价Pareto最优解;采用特殊拥挤距离非支配排序策略实现个体选优、精英学习策略避免过早收敛。通过在14个多模态多目标函数上进行测试,并与7种新提出的多模态多目标优化算法进行对比实验以及Wilcoxon秩和检验发现,CSSMPIO的总体性能优于对比算法。最后将算法用于基于地图的测试问题,进一步证明了算法的有效性。
