| GA与PSO解DE与LP问题的效率比较 |
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| 引用本文： | 庄思发.GA与PSO解DE与LP问题的效率比较[J].计算机系统应用,2016,25(6):244-248. |
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| 作者姓名： | 庄思发 |
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| 作者单位： | 韶关学院 数学与统计学院, 韶关 512005 |
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| 基金项目： | 江苏省高校自然科学研究项目(14KJB520036) |
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| 摘 要： | 遗传算法和粒子群算法都具有很强的搜索能力,在最优化问题中有着极其广泛的应用.文章针对常微分方程(DE)近似解和一般线性规划(LP)问题的解利用遗传算法和粒子群算法求解,深入的比较和分析了GA与PSO在这两种优化问题中的效率.在固定其他参数而调整群体数量的基础上比较了GA与PSO在微分方程近似解和LP问题解的优化能力.
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| 关 键 词： | 遗传算法 粒子群算法 常微分方程 线性规划 优化问题 |
| 收稿时间： | 2015/9/19 0:00:00 |
| 修稿时间： | 2015/11/13 0:00:00 |
Efficiency Comparison of GA and PSO on DE and LP Problem |
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| ZHUANG Si-Fa.Efficiency Comparison of GA and PSO on DE and LP Problem[J].Computer Systems& Applications,2016,25(6):244-248. |
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| Authors: | ZHUANG Si-Fa |
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| Affiliation: | School of Math & Statistics, Shaoguan University, Shaoguan 512005, China |
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| Abstract: | Genetic algorithm and Particle Swarm Optimization algorithm with strong search capability have a very wide range of applications in the optimization problem. This paper focuses on approximate solutions of ordinary differential equations and LP solutions, based on genetic algorithm and particle swarm algorithms, a comparison and analysis of the efficiency of two kinds of optimization problems is made. We then fix other parameters but adjust the particle population, in the purpose to compare optimization capability of GA and PSO in approximate solutions of differential equation and the LP problem. |
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| Keywords: | genetic algorithm particle swarm optimization differential equation liear program optimization problem |
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