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基于遗传算法的二维排样问题求解新策略
引用本文:张立驰,李健.基于遗传算法的二维排样问题求解新策略[J].南通职业大学学报,2009,23(3):93-97.
作者姓名:张立驰  李健
作者单位:1. 江苏大学,工商管理学院,江苏,镇江,212000;镇江高等专科学校,江苏,镇江,212000
2. 江苏大学,机械工程学院,江苏,镇江,212013
摘    要:针对采用自然编码的遗传算法在排样问题(CSP)过程中初始群体设置和交叉变异操作过于复杂的缺点,采用了顺序编码(Grefenstette编码)作为遗传算法编码方案,并对排样问题进行求解。采用这种遗传算法策略对CSP试算的结果表明,该策略利于排样问题的求解,算法操作简单,可推广应用到制造业及其他规划领域的排样规划中。

关 键 词:排样问题  资源优化  遗传算法

A new solution for two-dimensional cutting stocks problems based on generic algorithm
ZHANG Li-Chi,LI Jian.A new solution for two-dimensional cutting stocks problems based on generic algorithm[J].Journal of Nantong Vocational College,2009,23(3):93-97.
Authors:ZHANG Li-Chi  LI Jian
Institution:1. School of Business Administration, Jiangsu University, Zhenjiang 212000, China; 2. School of Mechanical Engineering, Jiangsu University, Zhenjiang 212013, China; 3. Zhenjiang College, Zhenjiang 212000, China)
Abstract:The Grefenstette coding is introduced to initialize the population for simplifying the initialization and keeping the diversity of the initialized population and the simplicity of the crossover operator and mutation operator in the generic algorithm(GA) for solving the cutting stock problems. Results show that this generic algorithm is suitable for solving cutting stocks problems (CSP) in the simple way and can be used to solve the problems encountered in path programming in machining field and other programming field.
Keywords:cutting stock problems  resource optimization  generic algorithm
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