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基于粒子群复形法优化复垦土地结构
引用本文:刘贺同,莫愿斌.基于粒子群复形法优化复垦土地结构[J].农业网络信息,2006(12):16-19.
作者姓名:刘贺同  莫愿斌
作者单位:1. 中国计量学院,理学院,浙江,杭州,310018
2. 中国计量学院,理学院,浙江,杭州,310018;浙江大学,智能信息研究所,浙江,杭州,310027
摘    要:针对我国人多地少、土地破坏的严重性,特别在矿区,破坏更为严重,及时恢复被破坏土地的使用价值对保持经济的持续发展是很必要的。在资金有限的情况下,如何合理地规划复垦土地的结构,一方面使土地复垦得以顺利地进行,另一方面又使经济效益达到最大化,是管理者所面临的问题。通过数学建模,这是一个带有约束条件的优化问题,针对这一问题,本文通过惩罚函数法把它化为无约束的优化问题,最后提出用粒子群算法改进的复形法进行求解。实例分析表明算法的有效性与简洁性,为复垦土地的结构优化提供一条有效的解决途径,增加规划的科学性、现实性和可操作性。

关 键 词:土地复垦  土地利用规划  约束条件  遗传算法  粒子群优化算法  优化设计
文章编号:1672-6251(2006)12-0016-04
修稿时间:2006年8月7日

Optimum design of reclamation land structure based on complex particle swarm optimization
LIU He-tong,MO Yuan-bin.Optimum design of reclamation land structure based on complex particle swarm optimization[J].Agriculture Network Information,2006(12):16-19.
Authors:LIU He-tong  MO Yuan-bin
Abstract:Aimed at the status there being many human being and little land,and lots of land having been seriously destroyed,especially in mining area in our country,it is necessary to resume the use value of the destroyed land for keeping economy continued development.For an administrator,he have to face a problem that how to reasonably plan the reclamation land structure so that reclamation can carry successfully out and the economic benefit reach maximum under limited funds.The model of this problem is an optimization problem with restricted condition in mathematics.In this paper,this problem was changed into no restricted optimization problem,and a Complex Particle Swarm Optimization Algorithm(CPSO) is put forward,which combined the advantages of Method of Complex(MC) and particle swarm optimization(PSO) in order to overcome PSO being easily trapped into local extreme value in optimizing multimodal function.The experimental results showed that the proposed algorithm is efficient,and it proved an effective way for Optimum Design of Reclamation Land Structure,and it enhanced the design scientific characters,feasibility and maneuverability.
Keywords:Reclamation land  Land use plan  Restricted condition  Genetic algorithm  Particle swarm optimization  Optimum design
本文献已被 CNKI 维普 万方数据 等数据库收录!
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