基于改进小生境免疫遗传算法的矩形件排样

journal6 ›› 2009, Vol. 30 ›› Issue (2): 55-57.

基于改进小生境免疫遗传算法的矩形件排样

（广州华南理工大学交通学院，广东广州 510641）

出版日期:2009-03-25 发布日期:2012-04-25
作者简介:梅颖（1978- ），女，江西南昌人，华南理工大学交通学院博士生，主要从事计算机辅助设计、制造及信息工程、计算机软件与理论研究.
基金资助:
广州科技项目资助（2002Z3-D3111）

An Improved Niche Immune Genetic Algorithm for Solving the Rectangle Packing Problem

(College of Transportation,South China University of Technology,Guangzhou 510641,China)

Online:2009-03-25 Published:2012-04-25

摘要/Abstract

摘要：讨论了基于改进小生境免疫遗传算法的矩形件排样问题，提出了基于排挤机制的小生境技术结合遗传算法的新思路，分别采用遗传算法、改进免疫遗传算法和小生境免疫遗传算法对大规模矩形件排样问题进行了实例比较分析，实例表明：在大规模矩形件排样过程中免疫算子和基于排挤机制小生境技术结合遗传算法的运用具有较好的全局寻优表现和收敛速度，算法有效、可行.

关键词： 排样优化, 小生境技术, 免疫遗传算法

Abstract: The paper discusses the rectangle packing problem based on an improved niche immune genetic algorithm,and a NIGA based on crowing mechanism is proposed.GA,an improved immune genetic algorithm,and NIGA are applied to practical experiments respectively to solve and optimize the packing problem,and the results are compared.In solving the large-scale rectangle packing problem,the application of immunity operator and niche genetic algorithm based on crowing mechanism improves the global optimization performance and velocity of convergence.The algorithm is effective and feasibility.

Key words: packing optimization, niche skill, immune genetic algorithm

梅颖. 基于改进小生境免疫遗传算法的矩形件排样[J]. journal6, 2009, 30(2): 55-57.

MEI Ying. An Improved Niche Immune Genetic Algorithm for Solving the Rectangle Packing Problem[J]. journal6, 2009, 30(2): 55-57.