摘要
针对集装箱配装问题这一NP-hard问题,提出了用于求解背包式强异类货箱的集装箱配装问题的memetic算法,该算法采用了“WB+DBL”的解码方式,并结合了常规遗传算法的广度搜索能力和局部搜索的深度搜索能力,能够有效地提高集装箱配装问题的求解质量。通过仿真实验,表明该算法是有效的。
The container loading problem is the problem of loading a subset of rectangular boxes into a rectangular container of fixed dimensions so that the volume of the packed boxes is maximized. The problem is known to be NP-hard. This paper presents a memetic algorithm for the container loading problem with boxes of different sizes. The ＂Wall Building＂ heuristic and the ＂Deepest Bottom Left＂ heuristic are used in decoding schema of the proposed algorithm. And the combination of genetic evolutionary and local search helps to improve the quality of the solutions. Simulation shows the effectiveness of the proposed algorithm.
出处
《辽宁工程技术大学学报（自然科学版）》
EI
CAS
北大核心
2006年第3期450-452,共3页
Journal of Liaoning Technical University (Natural Science)
基金
辽宁省教育厅科学研究计划基金资助项目(2005106)
