optimal basic solution 中文意思是什麼
optimal basic solution
解釋
最佳基本解-
Based on the multidisciplinary design optimization, a multidisciplinary variable coupling design optimization method for non - hierarchic systems was presented, and its basic ideas and working principle were given, to handle the coupling between subsystems, a coupling function was established by the ideal point during system - level coordination, which was used to coordinate independent optimization of the subsystem and finally obtain the global optimal solution
摘要基於多學科設計優化原理，提出了面向非層級復雜系統的多學科變量耦合優化設計方法，闡述了其優化設計的基本思路和工作原理通過設置理想耦合點，構造了耦合函數，使子系統在各自獨立優化設計的同時，在系統級的協調下達到耦合關系的滿足，並使系統得到總體上的優化。 -
It learns from the basic thought of hierarchical clustering methods ( hcm ), which groups objects by comparing the sizes of distance or similar coefficients between objects, meanwhile, combines with the optimal split - plot designs ( ospd ) in ordered samples, and synthesizes the intuitive property of hcm and the character of simplicity and the ability in finding out the accurate solution of ospd. with history data, this paper assumes that data from the same group come from the same distribution, and so do the history data
本文汲取了系統聚類法中通過定義距離或相似系數並以其大小將對象進行分類的基本思想，將之與有序樣本情況下的最優分割法相結合，吸收了系統聚類法的直觀性和最優分割法的簡捷性及可以求出精確最優解的良好性質，在存在歷史數據的條件下，假設同類數據來自於同一分佈，歷史數據相應的來自該分佈。 -
Finally, genetic optimization research is summarized on several typical production scheduling problems. after expounding the general idea of genetic algorithm, the comparative advantages in contrast to the traditional algorithm, the basic characteristics of genetic algorithm and its theoretical base, the paper puts emphasis on the efficiency of genetic algorithm in the scheduling of flow shop, and puts forward an improving genetic algorithm : the ordinal genetic algorithm based on the heuristic rules. the new algorithm introduces into the initial group the solution of heuristic algorithm, and in the group structure adopts a strategy of first ordering according to the priority of the adaptive solution, and then defining a new way of choosing probability by segments, which provides more hybridizing opportunity for optimized individuals, and designs variation - control rule to prevent single population and partial optimal solution
在論述了遺傳演算法的思想、與傳統搜索演算法的比較優勢、遺傳演算法的基本特徵和遺傳演算法的理論基礎（包括模式定理、隱含并行性、基因塊假設、欺騙問題和收斂性定理）后，重點探討了遺傳演算法在flowshop調度問題中的潛力和有效性；結合啟發式規則，提出了一個改進的遺傳演算法?基於啟發式規則的有序遺傳演算法，新演算法在初始種群中引入了啟發式演算法的解，在種群結構上採用了先按適應值優劣排序再分段確定選擇概率的新策略，使優質個體有更多的雜交機會，在變異中設計了變異控制規則，以防種群單一化，而陷入局部優化解。
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