adaptive scheduling algorithm 中文意思是什麼

adaptive scheduling algorithm 解釋
自適應調度演算法
  1. Kung, chih - hsien ; devaney, michael j. ; huang, chung - ming and kung, chih - ming, “ power source scheduling and adaptive load management via a genetic algorithm embedded neural network, ” the proceedings of the ieee instrumentation and measurement technology conference, baltimore, maryland, usa, may 1 - 4, 2000

    龔志賢，黃仲銘，龔志銘（民88 ） ， 」類神經網路應用於最佳化電力負載管理之研究」 ，第四屆人工智慧與應用研討會，大葉大學。
  2. And we also research on the job without resource requirement, and design proportional job scheduling algorithm. we also design the adaptive method of job execution, and through which the resource can be used more

    同時，也對作業無明確資源需求的情況進行研究，提出了按比例作業調度演算法，給出了演算法評價及改進方法。
  3. This paper use ga to figure out the complicated scheduling problem ; the main research concentrates on the following several aspects : ( 1 ) by reading a great deal of documents of scheduling problem and ga, the issue that genetic algorithm being adaptive to solve scheduling problem is introduced ; ( 2 ) hybrid genetic algorithm is adopted to solve a multi - objective job scheduling problem on identical parallel machine and a multi - objective job scheduling problem on non identical parallel machine, and the feasibility and validity of the algorithm is approved by numeric experiment ; ( 3 ) based on the heuristic algorithm of maximizing customer ' s satisfaction for single machine, this issue is extended to parallel machine, and then bring forward a heuristic arithmetic and a virus infective hybrid genetic algorithm

    本文應用遺傳演算法求解復雜的生產調度問題；主要在以下幾個方面作了一些研究工作：通過大量閱讀各種生產調度和遺傳演算法的文獻，指出了遺傳演算法適合解決生產調度問題。採用混合遺傳演算法應用在求解多目標等同并行多機問題和多目標非等同并行多機問題，並通過模擬實驗證明演算法的可行性和有效性。在求解極大化顧客滿意數的單機問題的啟發式演算法的基礎上，將此問題擴展為多機問題，提出一種啟發式演算法和一種帶病毒感染的混合遺傳演算法。
  4. Solving scheduling problems of rolling sequence with an adaptive genetic algorithm

    用自適應遺傳演算法求解軋制順序調度問題
  5. 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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