the integrated optimization procedure is also provided, which aimed at the least loss after the disqualification has happened 并給出了質(zhì)量出現(xiàn)問題后的偏優(yōu)調(diào)整算法,該算法可使該項目的綜合指標達到最優(yōu)或滿足用戶要求。
the combination of the ann model of the designer's preference and the optimization procedure in this method generates the intelligent guiding for the multiobjective optimization process, and compromise programming is also used to find the final solution 建立pareto解到其評分值的映射的神經(jīng)網(wǎng)絡(luò)模型,以表達設(shè)計者的偏好。該神經(jīng)網(wǎng)絡(luò)模型和優(yōu)化過程的結(jié)合,實現(xiàn)了精確尋優(yōu),并借助于折衷規(guī)劃得到最后的設(shè)計方案。
optimized association rules are permitted to contain uninstantiated attributes . the optimization procedure is to determine the instantiations such that some measures of the roles are maximized . this paper tries to maximize interest to find more interesting rules . on the other hand, the approach permits the optimized association rule to contain uninstantiated numeric attributes in both the antecedence and the consequence . a naive algorithm of finding such optimized rules can be got by a straightforward extension of the algorithm for only one numeric attribute . unfortunately, that results in a poor performance . a heuristic algorithm that finds the approximate optimal rules is proposed to improve the performance . the experiments with the synthetic data sets show the advantages of interest over confidence on finding interesting rules with two attributes . the experiments with real data set show the approximate linear scalability and good accuracy of the algorithm 優(yōu)化關(guān)聯(lián)規(guī)則允許在規(guī)則中包含未初始化的屬性.優(yōu)化過程就是確定對這些屬性進行初始化,使得某些度量最大化.最大化興趣度因子用來發(fā)現(xiàn)更加有趣的規(guī)則;另一方面,允許優(yōu)化規(guī)則在前提和結(jié)果中各包含一個未初始化的數(shù)值屬性.對那些處理一個數(shù)值屬性的算法進行直接的擴展,可以得到一個發(fā)現(xiàn)這種優(yōu)化規(guī)則的簡單算法.然而這種方法的性能很差,因此,為了改善性能,提出一種啟發(fā)式方法,它發(fā)現(xiàn)的是近似最優(yōu)的規(guī)則.在人造數(shù)據(jù)集上的實驗結(jié)果表明,當優(yōu)化規(guī)則包含兩個數(shù)值屬性時,優(yōu)化興趣度因子得到的規(guī)則比優(yōu)化可信度得到的規(guī)則更有趣.在真實數(shù)據(jù)集上的實驗結(jié)果表明,該算法具有近似線性的可擴展性和較好的精度
not only inter disciplinary design optimization was parallelized, but also inner disciplinary design optimization was executed in parallel, thus the optimization procedure can be speeded up greatly . the asynchronous parallel distributed coevolutionary mdo algorithm also has good flexibility, scalability and fault tolerance 不但實現(xiàn)了各學科的并行設(shè)計優(yōu)化,而且同一學科內(nèi)部也實現(xiàn)了并行優(yōu)化,從而能大大加快設(shè)計進程,同時具有很好的靈活性、可伸縮性和容錯性。
finally, considering the flight distance of every airline in the airline-network, using “ seat kilometre ” as the unit of the capacity, the paper optimized the capacity assignment in airline-network . as the result of above, types of aircraft and the amount of them, the flight frequency and types of aircraft were optimally constituted . the two preceding optimization procedures are all based on balance of capacity expenditure and the market share of airlines, aiming at the maximum profit in whole airline-network 三、對整個航線網(wǎng)絡(luò)進行運力的優(yōu)化分配,首先考慮整個航線網(wǎng)絡(luò)中具體每條航線的航程,以“座公里”作為運力單位進行,將運力在整個航線網(wǎng)絡(luò)上優(yōu)化分配,根據(jù)優(yōu)化得到結(jié)果和公司擁有的機型和每種機型的數(shù)量,再對每條航線的航班頻率和機型進行優(yōu)化組合。