Ant colony optimization ( aco ) algorithm is a nature - inspired metaheuristic algorithm . it has experienced more than 10 years ’ development since it was proposed and has become an efficient tool for solving combinatorial optimization problem 蟻群優(yōu)化算法是一種基于自然啟發(fā)的metaheuristic算法,從其提出到現在歷經10多年的發(fā)展到目前已經成為一種解決組合優(yōu)化問題的有效工具。
Dp technique is a high efficiency algorithm to solve combinatorial optimization problems by divided the multidimensional problem into multiple 1 - dimension problems . when this technique resorts to accumulate multiple frames , there are some disadvantages 動態(tài)規(guī)劃算法是一種解決組合尋優(yōu)問題的高效算法,通過將n維問題變換為n個一維優(yōu)化問題,一個一個地求解的方法,很好的提高了效率。
The maximum clique problem ( mcp ) is a classical combinatorial optimization problem which belongs to np - hard , and many practical problems can be formulated to it . therefore , studying the mcp is full of significance both in theory and in practice 最大團問題是一個經典的np難的組合優(yōu)化問題,很多實際問題都可以抽象為對無向圖上最大團問題的求解,所以,對最大團問題的研究無論在理論上還是實際上都有重要意義。
To solve the combinatorial optimization problem of outer layout and inner connection integrated schemes in the design of hydraulic manifold blocks ( hmb ) , an intelligent virtual design method was proposed with combining modern intelligent optimization methods with virtual design technology 摘要為解決液壓集成塊設計中外部布局和內部布孔集成的組合優(yōu)化問題,提出了一種融合現代智能優(yōu)化方法和虛擬設計技術的智能虛擬設計方法。
Ant colony algorithm is a novel simulated evolutionary algorithm , which is used to solve the optimization problems through simulating the way of ants finding the shortest path for food . this algorithm has been applied successfully to combinatorial optimization problems such as traveling salesman problem 蟻群算法是一種新型的模擬進化算法,它通過模擬蟻群在覓食過程中尋找最短路徑的方法來求解優(yōu)化問題,目前在旅行商問題等組合優(yōu)化問題中有成功的應用。