摘要
针对工程实际中常见的多规格一维型材下料问题,本文根据原材料数量是否满足下料要求将该问题分为完全下料和不完全下料两方面,分别建立优化模型。在传统遗传算法的基础上,引入FFD、BF近似算法的思想,提出求解该类问题的混合遗传算法,并编制相应软件。最后给出一个工程项目的下料算例,实际使用表明,本文方法的效果是令人满意的。
The efficientcy of variable-sized inventory of one-dimensional cutting stock, such as angle iron, is of great practical significance in the industries. Any improvement is important, since even small improvement in the cutting scheme will result in large savings of raw material and energy when the amount of produced material is huge. This paper divides the problem into two aspects, fully cutting and partly cutting, and optimization models for them are built. A hybrid genetic algorithm combining with the FFD and BF heuristic method is presented as a solution to the optimization problems. The computer program was developed. One sample for a steel structure is presented and solved. The result was satisfactory that overall raw material needed by all cuts is minimized.
出处
《机械科学与技术》
CSCD
北大核心
2003年第S2期80-83,86,共5页
Mechanical Science and Technology for Aerospace Engineering
关键词
多规格型材下料
优化
混合遗传算法
Variable-sized inventory
One-dimensional cutting
Optimization
Hybrid genetic algorithm
