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遗传、禁忌、模拟退火等算法求解背包问题C-Genetic, contraindications, simulated annealing algorithm for knapsack problem C++
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vc++中用以测试mpi并行的遗传算法，应用在0-1背包的问题中。-Vc++ is used to test the mpi parallel genetic algorithm (ga), used in 0-1 knapsack problem.
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python遗传算法求解背包问题,后者由1978年由Merkel和Hellman提出。其运行依赖DEAP
-python genetic algorithm knapsack problem, which in 1978 proposed by Merkel and Hellman. Its operation depend DEAP
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背包问题_遗传算法解决,matlab例程，数学建模常用算法-Genetic algorithm to solve knapsack problem _, matlab routines, mathematical modeling algorithms
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matlab代码遗传算法解决背包问题，0-1整数规划问题-Genetic algorithm to solve knapsack problem, 01 integer programming problem
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Matlab 代码，用遗传算法解决01背包问题-Matlab code, using genetic algorithms to solve knapsack problem 01
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此程序采用了免疫遗传算法求解背包问题，其中重要参数都有说明。-Immune genetic algorithm has been developed to handle the knapsack problem, the important parameters have been described in the program
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背包问题用遗传算法解决的一个例子-An example of using genetic algorithms to solve knapsack problem of
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遗传算法求解背包问题,基本的遗传算法，采用顺序编码-Genetic algorithm for solving knapsack problem，the basic genetic algorithm, using the coding sequence
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1.用模拟退火解决TSP问题
2.用遗传算法解决0/1背包问题-1. solve TSP problem using simulated annealing 2. 0/1 knapsack problem solved using genetic algorithms
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遗传算法用于求解多目标背包问题，学包括基本的选择、杂交、变异等遗传算子.-Genetic algorithm for solving multi-objective knapsack problem, learning the basic choice, hybridization, mutation and other genetic operators.
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遗传算法在旅行商问题下的一种应用代码，一种能够解决多维背包问题的应用代码。-Genetic algorithm in the traveling salesman problem of a kind of application code, one can solve the multi-dimensional knapsack problem application code.
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量子遗传算法解决0-1背包问题的MATLAB代码，亲测好用-Quantum genetic algorithm to solve 0-1 knapsack problem MATLAB code, useful pro-test
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通过Java编码实现标准遗传算法（SGA）解决背包问题(Through Java coding, the standard genetic algorithm (SGA) is implemented to solve knapsack problem)
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使用传统的遗传算法解决0-1背包问题，其中使用的是轮盘选择、最简单的随机交叉变异(Using traditional genetic algorithm to solve the 0-1 knapsack problem)
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遗传算法解决背包问题，matlab环境实现c流程(Solving knapsack problem by genetic algorithm)
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利用遗传算法解决背包问题给定10个物品及其重量，放入总重量为25的背包(Using genetic algorithm to solve knapsack problem, give 10 items and their weight, and put them in a total weight of 25 knapsack.)
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能根据输入的范围计算y=x^2的最优值，以及解决背包问题的遗传算法(It can calculate the optimal value of y=x^2 according to the input range as well as solve the knapsack problem by genetic algorithm.)
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使用遗传算法解决01背包问题，并输出得到最大价值的遗传代数以及每一代的最大价值(Using genetic algorithm to solve 01 knapsack problem)
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使用遗传算法解决0-1背包问题，调试成功，非常适合初学者了解遗传算法和0-1背包问题(Using genetic algorithm to solve 0-1 knapsack problem, debugging is successful. It is very suitable for beginners to understand genetic algorithm and 0-1 knapsack problem.)
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