Solving the Container Pre-Marshalling Problem Using Artificial Bee Colony Algorithm

Ricardo Soto, Broderick Crawford, Cristian Galleguillos, C. Montiel, Rodrigo Olivares, G. Cabrera
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引用次数: 1

Abstract

In a container terminal occurs the Container Pre-Marshalling Problem (CPMP), which deals with the necessity of the container reshuffling in order to reduce the later movements when containers must be retrieved. Then, CPMP is a minimization problem for finding a reshuffling sequence from an initial bay layout (disordered) to a final bay layout (ordered) according to certain conditions that must satisfy the retrieve preferences of containers. This problem is known to be NP-Hard, therefore solving such as problem could be a very hard task and extremely complex, with high execution time and use of computational resources. Thus using metaheuristics approaches could be a good choice for tackling this problem. We have selected the Artificial Bee Colony algorithm for tackling the CPMP, showing good results that competes the state of the art works in regards of its solution qualities.
用人工蜂群算法求解容器预编组问题
集装箱码头中存在集装箱预编组问题(container Pre-Marshalling Problem, CPMP),该问题处理的是集装箱重新洗漱的必要性,以便在必须提取集装箱时减少后续移动。然后,CPMP是一个最小化问题,它根据一定的条件找到从初始舱位布局(无序)到最终舱位布局(有序)的重组序列,这些条件必须满足容器的检索偏好。这个问题被称为NP-Hard,因此解决这样的问题可能是一个非常困难和极其复杂的任务,具有很高的执行时间和计算资源的使用。因此,使用元启发式方法可能是解决这个问题的一个很好的选择。我们选择了人工蜂群算法来解决CPMP,在解决质量方面显示出良好的结果,与目前的艺术作品相竞争。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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