pareto optimization 中文意思是什麼
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Based on result of the multiple objective optimization, this dissertation investigates the multiple objective decision of mixed - model flow m anufacturing system. in allusion to the pareto frontier, in terms to the assistant information of decision schemes, the preference of objectives, the preference of decision schemes, individual decision - making and group decision - making are gained through the measure function, 0 - 1 programming and relative entropy combining with subjective and objective factors
在多目標優化的基礎上，研究了混合流水生產系統的多目標決策問題，針對多目標協同優化得到的pareto前端，依據決策方案的輔助信息、對指標有偏好的信息以及對決策方案有偏好的信息等，採用測度函數、 0 - 1規劃方法以及相對熵的方法，結合主客觀因素進行多目標個體決策和群體決策，把多目標優化與多目標決策聯系起來。 -
After analyzing the dual - nature of finance resources, the author analysis the issue of financial resources allocation and the allocation efficiency. the paper also highlights the importance of the optimization of financial resource allocation and the improvement of allocation efficiency. pareto optimality is a central concept of new welfare economics, which can be used to judge whether resource allocation is on optimal state in a society
本文提出了對金融資源和金融資源配置效率的理解，簡要介紹衡量金融資源配置效率的帕累托最優標準，同時將假設前提放寬到我國的市場經濟條件，研究分析影響金融資源配置的現實因素及約束條件，並將約束條件系統化，提出衡量金融資源配置狀態的指標體系。 -
Key techniques and main measures that apply genetic algorithm ( ga ) to multiobjective search are studied. based on the comparison of various multiobjective optimization ga ( moga ), a new algorithm called improved pareto ga ( ipga ) that combines the nsga - ii and local search algorithm is presented
研究了遺傳演算法應用於多目標搜索的關鍵技術及主要解決措施，比較分析了幾種主要的多目標遺傳演算法的優缺點，提出了一種改進的多目標遺傳演算法（ ipga ） 。 -
It is widely applied to the domain of combinational evolutionary problem seeking, self - adapt controlling, planning devising, machine learning and artificial life etc. however, there are multi - objective attributes in real - world optimization problems that always conflict, so the multi - objective genetic algorithm ( moga ) is put forward. moga can deal simultaneously with many objections, and find gradually pareto - optimal solutions
由於現實世界中存在的問題往往呈現為多目標屬性，而且需要優化的多個目標之間又是相互沖突的，從而多目標遺傳演算法應運而生，它使得進化群體并行搜尋多個目標，並逐漸找到問題的最優解。 -
Comparison and contrast on search space of the sga and full dominance - recessive diploid ga justifies the latter ' s capability to search hi a larger representation space. when applied to practical multi - objective design optimization, the proposed ga obtains a set of desired pareto solutions
將完全顯隱性二倍體遺傳演算法應用於一個帶約束的多目標結構優化設計問題之中，得到了一組pareto解，為遺傳演算法與多目標結構優化設計的結合作了有益的嘗試。 -
Pareto optimization on electricity price discount considering demand price elasticity
考慮需求價格彈性的銷售電價帕累托優化折扣 -
At first, it uses the nsga - ii for obtaining the approximate pareto optimization solutions. then, local search is run with previous each solution to find a better solution using the mode search algorithm
該演算法首先利用nsga -演算法得到近似的pareto最優解；然後以增廣的加權tchebycheff方程作為評價函數，採用模式搜索法對由nsga -演算法得到的每個解再進行局部優化。 -
From the economical point of view, the philosophical system, principles and methods concerning the fair allocation of resources were further researched. the allocation scheme of current american national airspace resource was proposed by utilizing the theory of priority assignment, pareto optimization and proportion distribution
然後重點針對cdm下的國家空域資源分配問題在理論和實踐上進行探討，從經濟學的角度深入研究了公平分配資源的哲學體系、原則和方法，利用優先級分配理論、最優理論及比例分配分配理論對目前的美國國家空域資源分配方案進行了研究。 -
The algorithm is a new multi - objective optimization evolutionary algorithm using elitism, in which fine - grained fitness assignment strategy, a density estimation technique, and an enhanced archive truncation method are used. the algorithm can converge to the pareto optimal solutions rapidly and the non - dominated solutions gain better distribution and spread
Spea2演算法是一種新的使用了精英機制的多目標優化演化演算法，它採用了細粒度賦值策略和密度估計技術，整個演算法可以快速收斂到pareto最優解，並且可以獲得很好的分佈性和延展性。 -
Optimization for composite wing based on pareto genetic algorithm
遺傳演算法的復合材料機翼優化設計 -
In the present paper, the problem is solved with a multi - objective genetic algorithm ( ga ) optimization method combined with linear programming ( lp ) and a group of pareto solutions are provided
採用多目標遺傳演算法和線性規劃相結合的方法求解出間歇化工過程優化設計模型的非劣解集，並與不同權重系數下的單目標算例進行了比較。 -
The solution of the optimization control problem can be approached by a fuzzy control algorithm based on the pareto rule base
該多目標控制問題的最優解即最優控制函數，可利用基於該規則基的模糊控制演算法進行逼近。 -
In fact, various evolutionary approaches to multi - objective optimization have been proposed since 1985, capable of searching for multiple pareto optimal solutions concurrently in a single simulation run. spea2 is one of the art of the date algorithms
實際上，自從1985年以來，研究者們已經提出了許多基於演化計算的多目標優化演算法，這些演算法能夠在一次獨立的運行中同時搜索到多個pareto最優解。 -
Computing result shows that : coevolutionary mdo algorithms are effective on this problem ; distributed coevolutionary mdo algorithm is better than cooperate coevolutionary mdo algorithm ; asynchronous parallel version of distributed coevolutionary mdo algorithm speeds up the optimization procedure greatly while maintains good convergence performance ; multiobjective distributed coevolutionary mdo algorithm approximates the whole pareto optimal front well in only one single run, saves much computing cost than constraint method to obtain pareto optimal set, and greatly shortens search time by distributed asyn
計算結果表明：協同進化mdo演算法求解該問題是有效的，其中分散式協同進化mdo演算法優于合作協同進化mdo演算法；異步并行的分散式協同進化mdo演算法在保證收斂性能的同時大大加快了優化進程；多目標的分散式協同進化mdo演算法僅一次運行就很好的逼近了問題的整個pareto最優前沿，比用約束法求解pareto最優集節省了大量計算開銷，而且通過網路多臺微機的分散式并行執行大大縮短了搜索時間。
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