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。
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.
出处
《南通职业大学学报》
2009年第3期93-97,共5页
Journal of Nantong Vocational University
关键词
排样问题
资源优化
遗传算法
cutting stock problems
resource optimization
generic algorithm
