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本程序利用遗传算法解决背包文件问题。本程序利用遗传算法解决背包文件问题。-This procedure using the genetic algorithm to solve knapsack problem document. This procedure using the genetic algorithm to solve knapsack problem document.
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采用遗传算法解决0-1背包问题，即装入物体容量有限，每个物体有不同价值，使得最终价值最高-Using genetic algorithm to solve the 0-1 knapsack problem, that is, limited capacity into objects, each object has a different value, making the final value of the maximum
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Knapsack Problem - Genetic Algorithm. Results can be compared with optimal value obtained from function using Dynamic Programming.
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本程序将遗传算法应用于背包问题。借助了大自然的演化过程,是多线索而非单线索的全局优化方法,采用的是种群和随机搜索机制. -This procedure will be applied to knapsack problem genetic algorithm. With the evolution of nature, is more than a single clue leads the global optimization method, using population and ran
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背包问题，用遗传算法解决，并在VC++环境下调试通过，得到正确结果，可供参考，源码C文件中有较详细的注释-Knapsack problem, using genetic algorithm, and in the VC++ debugging environment through, get the correct results, for reference, source C files in more detailed comments
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利用遗传算法解决的背包问题，程序开发环境：Visual C++6.0-Using genetic algorithm to solve the knapsack problem, program development environment: Visual C++6.0
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用遗传算法计算背包问题的经典程序,word的文档里面有说明和程序。-Knapsack problem using genetic algorithm the classic program, word document which has instructions and procedures.
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主要采用遗传算法解决背包问题。是值得学习算法。-By using the genetic algorithm to solve the main knapsack problem. Is worth learning algorithm.
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用遗传算法求解背包问题，用启发式算法求解背包问题。-Knapsack problem using genetic algorithm, heuristic algorithm for solving knapsack problem.
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用遗传算法解决0_1背包问题，比较经典,适合做参考论文-0_1 knapsack problem solving using genetic algorithms, more classic, suitable reference paper
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使用遗传算法解决经典的背包问题，即整数规划问题。-Using genetic algorithm to solve the classic knapsack problem, that is, the problem of integer programming.
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Binary Knapsack Problem implementation using Genetic Algorithm.
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binary knapsack problem using genetic algorithm
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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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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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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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