Description: 用群智能改进禁忌搜索算法在多用户检测中的应用，希望有人能用得到-Swarm - Tabu Search Algorithm in multi-user detection of hope that someone can be used to be Platform: |
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Author:hello |
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Description: 用群智能改进禁忌搜索算法在多用户检测中的应用，希望有人能用得到-Swarm- Tabu Search Algorithm in multi-user detection of hope that someone can be used to be Platform: |
Size: 134144 |
Author:hello |
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Description: 利用粒子群算法求解VRP问题程序，其中和禁忌搜索算法结合成混合算法求解，-The use of particle swarm optimization procedure for solving VRP problems, including tabu search algorithm and combined into a hybrid algorithm, Platform: |
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Author:zcx |
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Description: 现代最优化算法（有170多页的PPT，2010年的）
分为三个部分
Part 1 概论
Part 2 模拟退火算法
Part 3 遗传算法
现在常用的优化算法
禁忌搜索算法
模拟退火算法
遗传算法
人工神经网络
蚁群算法
粒子群算法
混合算法-Modern optimization algorithm is divided into three parts Part 1 Part 2 Introduction Part 3 simulated annealing genetic algorithm optimization is now commonly used in tabu search algorithm simulated annealing genetic algorithm, artificial neural network hybrid particle swarm ant colony optimization algorithm Platform: |
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Author:zhang |
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Description: 提出一种基于改进粒子群动态搜索算法的网络重构方法，算法把初始粒子群按照适应度的大小分为两个互不交叉，且具有不同分工的子群，并进行动态搜索。通过引入了交叉和禁忌思想，减少了解陷入局部最优的可能性．与遗传、禁忌搜索算法重构的结果进行比较，表明本文算法具有更高的搜索效率，更容易找到全局最优解．-：An improved method based on improved particle swarm optimization dynamic search algodthm networkrcconfiguration
is presented in this paper．The initial particle swarm is divided into two different subgroups according to the size of fitness，with a division of labour between the different subgroups of dynamic search．Cross
thinking and ideological tabu ale ledinto this algorithm to reduce the possibility of local Optimum．Compared with genetic and tabu search algorithm,the results show that the proposed method possesses a hi．gher search efficiency andis easier tO find the global optimum solutions． Platform: |
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Author:yirufang |
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Description: SP(旅行商)问题代表组合优化问题,具有很强的工程背景和实际应用价值,但至今尚未找到非常有效的
求解方法.为此,讨论了最近研究比较热门的使用各种智能优化算法(蚁群算法、遗传算法、模拟退火算法、禁忌搜索
算法、Hopfield神经网络、粒子群优化算法、免疫算法等)求解 TSP问题的研究进展,指出了各种方法的优缺点和改
进策略.最后总结并提出了智能优化算法求解 TSP问题的未来研究方向和建议.
-Traveling salesman problem (TSP) is the representation of a kind of combination optimization problems,
possessing a strong engineering background and practical application value. However, there is no effective corre
2 sponding solution to it. A im at that, the research and application of themostpopularmeta
2heuristicmethods such as ant colony algorithm, genetic algorithm, simulated annealing, tabu search, hopfield neural network, particle swarm optimization and immune algorithm, etc. are reviewed. The advantages and disadvantages of each method and the improvement strategies are discussed. The future research direction and sug
Platform: |
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Author:chenchen |
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Description: System reliability analysis and optimization are important to efficiently utilize available resources and to develop an optimal system design architecture. System reliability optimization has been solved by using optimization techniques including meta-heuristics. Meanwhile, the development of meta-heuristics has been an active research field of the reliability optimization wherein the redundancy, the component reliability,
or both are to be determined. In recent years, a broad class of stochastic meta-heuristics, such as simulated annealing, genetic algorithm, tabu search, ant colony, and particle swarm optimization paradigms,has been developed for reliability-redundancy optimization of systems. Platform: |
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Author:ali |
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Search - tabu search swarm