本文提出了一种基于分布估计的离散粒子群优化算法。
This paper will give a scheme of intelligent test paper based on the estimation of distribution of discrete particle swarm algorithm.
通过自适应的离散粒子群算法来对核相似矩阵进行学习。
Uses the adaptive discrete particle swarm algorithm to learn the similar kernel matrix.
提出了一种求解置换流水车间调度问题的离散粒子群优化算法。
Solving Rectangular Packing Problem Based on Discrete Particle Swarm Optimization Algorithm;
提出了一种基于离散粒子群优化算法求解矩形件排样问题的方法。
A discrete particle swarm algorithm for the rectangular strip packing problem is presented.
文中提出了一种基于改进离散粒子群优化算法求解机组组合问题的新方法。
A solution to unit commitment via an enhanced binary particle swarm optimization (BPSO) algorithm is presented.
借鉴蚁群算法的信息素机制,提出了一种基于信息素机制的离散粒子群算法。
A pheromone-based discrete particle swarm optimization algorithm was proposed borrowing the idea of pheromone refresh mechanism of ant colony algorithm.
同时,针对整数资源分配这类组合优化问题,提出了相应的离散粒子群算法。
At the same time, a corresponding particle swarm optimization algorithm is presented to solve the optimization problem of integer resource allocation. This algorithm is easy to programming.
在求解冷负荷启动中的配电网馈线供电恢复问题时引入了离散粒子群优化算法并对该算法进行了改进。
Here, discrete particle swam optimization algorithm is introduced to solve the problem of optimal restoration of distribution feeders during cold load pickup.
针对不同的网络实际条件,提出一种改进的离散粒子群算法来寻找网络中任意两个节点间的最优路由。
In this paper, a new routing approach based on discrete particle swarm optimization algorithm is briefly discussed to obtain the optimum path between two nodes in the network.
郭文忠,陈国龙。离散粒子群优化算法及其应用[M]。北京:清华大学出版社,2012:5 - 6。
GUO w, CHEN G. Discrete particle swarm optimization algorithm and its application [m]. Beijing: Tsinghua University Press, 2012:5-6.
根据限流措施优化配置问题的特点,提出先对候选可开断支路采用枚举法求解支路开断的优化方案,再采用改进离散粒子群算法(MDPSO)求解综合限流方案。
An enumeration method was used to get the optimal splitting of the candidate branches. A modified discrete particle swarm optimization algorithm (MDPSO) was used to get the final strategy.
提出了用于解决作业车间调度问题的离散版粒子群算法。
A discrete Particle Swarm Optimization (PSO) algorithm was presented for Job Shop scheduling problem.
粒子群算法在求解连续函数优化问题中取得了广泛的应用,但是其在离散的组合优化问题中的运用还比较少。
Particle swarm optimization is widely used to solve continuous function optimization issue, but its application in discrete combination optimization problems is still relatively few.
采用二分策略,通过最大化模块密度,提出了基于离散量子粒子群优化进行复杂网络社区检测的算法。
With bi-partitioning strategy, by maximizing the module density, an algorithm is proposed based on discrete quantum particle swarm optimization for complex network community detection.
本文将进化算法引入飞机排班问题,研究并实现了基于离散型粒子群算法的飞机排班系统。
This thesis introduces Discrete Particle Swarm Optimizer (DPSO) Algorithm to solve the fleet assignment problem. Firstly, the characterization of the fleet assignment is analyzed.
在基本粒子群算法的基础上,引入了惯性因子,并对离散变量进行了处理,直接构造了离散解值集和离散速度值集。
Based on the PSO, we introduce the inertia factor and construct the discrete position set and the discrete speed set, express the discrete variables accurately.
分析量子计算的特点,对量子旋转门进行研究,给出了新的量子旋转门调整策略,并与离散二进制粒子群优化算法进行组合,提出了二进制量子粒子群优化算法。
According to the analysis of the characteristics of quantum computing and the research of quantum rotation gate, a new quantum rotation gate adjustment strategy was introduced.
提出了用于解决作业车间调度问题的离散版粒子群算法。
This paper proposes a method of adaptive neural network based on constraint satisfaction for Job Shop Scheduling Problem.
提出了用于解决作业车间调度问题的离散版粒子群算法。
This paper proposes a method of adaptive neural network based on constraint satisfaction for Job Shop Scheduling Problem.
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