三维装箱问题的混合遗传算法

Hongfeng Wang, Yanjie Chen
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引用次数: 24

摘要

三维装箱问题由于其在许多实际应用中的通用性,引起了国内外学者的广泛关注。本文提出了一种用于3DBPP的混合遗传算法。在该算法的框架内,设计了一种特殊的个体二倍体表示方案,并采用启发式填充方法,该方法由左下最深处填充方法导出,完成了个体到解的转换。为了进一步提高算法的性能,本文还设计了几种特殊的遗传算法运算。对一组3DBPP测试问题的实验研究表明,该算法具有较好的有效性和适应性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A hybrid genetic algorithm for 3D bin packing problems
3D bin packing problem has attracted the wide concern from OR community due to their generalization in many realistic applications. In this paper, a hybrid genetic algorithm is proposed for 3DBPP. Within the framework of the proposed algorithm, a special diploid representation scheme of individual is designed and the heuristic packing methods, which are derived from a deepest bottom left with fill packing method, are employed to accomplish the translation from the individual to a solution. In order to further improve the performance of algorithm, several special GA operations are also designed in this paper. An experimental study over a set of 3DBPP test problems shows that the proposed algorithm is efficient and adaptable to address 3DBPP.
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