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首页> 外文会议>International conference on evolutionary multi-criterion optimization >Dealing with Scarce Optimization Time in Complex Logistics Optimization: A Study on the Biobjective Swap-Body Inventory Routing Problem
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Dealing with Scarce Optimization Time in Complex Logistics Optimization: A Study on the Biobjective Swap-Body Inventory Routing Problem

机译：复杂物流优化中的稀缺优化时间处理：双目标交换主体库存路由问题研究

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摘要

In this paper a biobjective Swap Body Inventory Routing Problem (SB-IRP) is considered: A combination of the Swap Body Vehicle Routing Problem (SB-VRP), which minimizes fixed and variable routing costs, and the Inventory Routing Problem (IRP). The problem is based on the context of the VeRoLog Solver Challenge 2014, where our proposed VeRoLog Solver was ranked third, and our previous work on the IRP. Since we are investigating a multi-period problem, an additional objective function is formulated which includes inventory levels at the customers. Dealing with the allocation of scarce optimization time to the VeRoLog Solver is an essential topic, since an alternating approach of the determination of a replenishment strategy and the routing is considered. We propose an Iterative Variable Neighborhood Search and analyze the allocation of the computational time by extended VeRoLog test instances.
机译：在本文中，考虑了双目标交换车身库存路由问题（SB-IRP）：交换车身车辆路由问题（SB-VRP）和库存路由问题（IRP）的组合，它使固定和可变路由成本最小化。该问题基于2014年VeRoLog解算器挑战赛的背景，我们提出的VeRoLog解算器排名第三，我们之前在IRP方面的工作也是如此。由于我们正在调查一个多期间的问题，因此制定了一个附加的目标函数，其中包括客户的库存水平。处理稀缺的优化时间给VeRoLog解算器的分配是必不可少的主题，因为考虑了确定补货策略和工艺路线的交替方法。我们提出了一个迭代变量邻域搜索，并通过扩展的VeRoLog测试实例来分析计算时间的分配。

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