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tabu algorithm    
相关语句
  禁忌算法
    Application of Improved Tabu Algorithm on Reactive Optimization
    改进禁忌算法在无功优化中的应用
短句来源
  禁忌算法
    Application of Improved Tabu Algorithm on Reactive Optimization
    改进禁忌算法在无功优化中的应用
短句来源
  禁忌搜索算法
    In allusion to genetic algorithms is subjected to premature, we utilize the main frame of parallel search supplied by the genetic algorithm and the tabu algorithm .
    针对遗传算法易产生过早收敛等缺点,提出一种将局部搜索能力强的禁忌搜索算法嵌入到遗传算法中的改进算法。
短句来源
  禁忌算法
    Application of Improved Tabu Algorithm on Reactive Optimization
    改进禁忌算法在无功优化中的应用
短句来源

 

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  tabu algorithm
Empirical evidence shows that the Tabu algorithm is very competitive by giving the best solutions to the tested instances.
      
A "Logic-Constrained" Knapsack Formulation and a Tabu Algorithm for the Daily Photograph Scheduling of an Earth Observation Sate
      
Methods to reduce execution time of the genetic algorithm, including the use of a Tabu algorithm for training data selection, are also discussed.
      
Before optimizing the rotor slots with genetic algorithm (GA), the second part is solved with TABU algorithm to simplify the problem.
      
The fact that the tabu algorithm controls its search by modifying mobilities provides several important benefits.
      


The paper design a genetic algorithm based on the tabu search. By utilizing the main frame of parallel search supplied by the genetic algorithm and the individual serial search mode of the tabu algorithm, this method can enlarge the search space and swiftly implement the overall optimization. If it is combined with the heuristics algorithm to solve the knapsack problem, according to the results of computer simulation, it can effectively improve the index of optimization performance and search efficiency....

The paper design a genetic algorithm based on the tabu search. By utilizing the main frame of parallel search supplied by the genetic algorithm and the individual serial search mode of the tabu algorithm, this method can enlarge the search space and swiftly implement the overall optimization. If it is combined with the heuristics algorithm to solve the knapsack problem, according to the results of computer simulation, it can effectively improve the index of optimization performance and search efficiency.

设计了一种基于禁忌搜索的遗传算法,利用遗传算法提供的并行搜索主框架,结合禁忌算法的个体串行搜索方式,能扩大搜索空间,快速实现全局优化。把基于禁忌搜索的遗传算法与启发式方法相结合用来求解背包问题,经过计算机仿真,其优化性能指标及搜索效率均有大幅度的提高。

In order to optimize the production of capacity constraints resource(CCR) in Drum-Buffer-Rope(DBR) theory,back-scheduling method with EDD or SPT rule is used to level the ruins of CCR.The sequence of orders after being leveled is used as the initial solutions.At the same time,the mixed objective functions of CCR are also given,that is,enhancing throughput and the on-delivery rate.Finally,tabu algorithm is proposed to optimize the production of CCR.Results of the example prove the validity of this method....

In order to optimize the production of capacity constraints resource(CCR) in Drum-Buffer-Rope(DBR) theory,back-scheduling method with EDD or SPT rule is used to level the ruins of CCR.The sequence of orders after being leveled is used as the initial solutions.At the same time,the mixed objective functions of CCR are also given,that is,enhancing throughput and the on-delivery rate.Finally,tabu algorithm is proposed to optimize the production of CCR.Results of the example prove the validity of this method.

为优化D rum-Buffer-Rope(DBR)理论中的瓶颈资源的生产安排,首先采用后推方法,利用传统的EDD或SPT法则对瓶颈资源上的负荷堆积进行推平,将推平后的订单加工顺序作为禁忌算法的初始解。同时,给出了瓶颈作业的双目标函数,即提高瓶颈产出率的同时减少订单延迟时间。在此基础上,利用禁忌优化算法,对瓶颈作业安排进行优化。算例结果充分证明了该方法的有效性。

This paper proposes a method for reactive optimization based on improved tabu algorithm.This method not only doesn't have special demand on original solve,but also decreases the number of solves which meet constraint condition in candidate sets.Slope climbing problem is settled by this method under the situation of high precision at the same time.At last,the advantage of this method is validated on IEEE30 bus system.

提出一种基于改进禁忌算法的无功优化方法,该算法不仅对初值没有特殊要求,而且减少了在候选解集中为了达到一定数量满足约束的个体而进行的大量搜索与计算;同时解决了禁忌算法在高精度情形下,无法爬坡的缺点。最后在IEEE30节点系统上验证了该算法的优越性。

 
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