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A novel mathematical model and a large neighborhood search algorithm for container drayage operations with multi-resource constraints

机译:一种新的数学模型和具有多资源约束的容器Drayage操作的大邻域搜索算法

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摘要

Multi-resource constraints in container drayage operations exist widely in real-life scenarios but have been seldom reported in literature. This study mainly addresses a container drayage problem with a limited number of empty containers at depots, with the goal of minimizing both the number of trucks in operation and the total working time of trucks. The problem is firstly formulated as a bi-objective mathematical model based on a so-called determined-activities-on-vertex graph. Three schemes are proposed to handle the developed mathematical model as: (a) a nonlinear constraint is linearized; (b) a parameter that is a large enough constant in the model is analyzed and tuned deeply; and (c) the bi-objective model is converted into a single-objective model. Furthermore, a large neighborhood search algorithm is designed to solve the problem. The two solution methods are validated and evaluated based on randomly generated instances as well as instances from literature. Numerical experimental results indicate that the methods can provide optimal or near-optimal solutions for medium- and large-scale instances in a short running time.
机译:集装箱DRAYAGE运营中的多资源限制在现实生活方案中广泛存在,但在文献中很少报告。本研究主要在仓库提供有限数量的空集装箱的集装箱Drayage问题,目的是最大限度地减少运行中的卡车数量和卡车总工作时间。该问题首先基于所谓的确定活动 - 顶点图形作为双目标数学模型。提出三种方案来处理所发育的数学模型,如下:(a)非线性约束是线性化的; (b)深入分析模型中足够大的参数,并深入调整; (c)双目标模型转换成单个目标模型。此外,设计了一个大的邻域搜索算法来解决问题。两种解决方案方法是基于随机生成的实例以及文献的实例进行了验证和评估。数值实验结果表明,该方法可以在短时间内为中型和大型实例提供最佳或接近最佳解决方案。

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