请登录 0 购物车
首页 图书 电子图书 期刊 参考文献及会议录 作者,编辑,审稿 A-Z 产品目录
Flexible Automation and Integrated Manufacturing 1999

ISBN 打印: 978-1-56700-133-4

GARP: GENETIC ALGORITHM FOR PART PACKING IN A RAPID PROTOTYPING MACHINE

Abstract

A unique three-dimensional packing problem with non-convex parts and without a gravity constraint can be defined in a selective laser sintering rapid prototyping machine. The goal for the packing task is to pack the parts to be manufactured as tightly as possible to maximize volume and machine time utilization. A genetic algorithm is used as a search engine to find a good packing pattern for parts. Each individual in a population represents one packing solution. The chromosomal representation is a three-dimensional ordered list of integers where each sublist has a different allele set. A fitness function simulates the packing of parts and also evaluates the quality of a solution. To calculate part intersections, the fitness function uses methods common in computational geometry. Due to the chromosome structure used, there is a lack of genetic material in the population. Methods to introduce new material into the population are defined and tested. Experiments with more difficult packing problems, where all parts are complex in shape, prove that the developed genetic algorithm is robust and able to find a good solution in most problem instances.
首页 Begell 数字门户 Begell数据库 期刊 图书 电子图书 参考文献及会议录 作者,编辑,审稿 A-Z 产品目录 订购及政策 关于BegellHouse 联系我们 Language English 中文 Русский 日本語 Português Deutsch Français Español